Eduardo Izquierdo’s research notebook

For the last couple of months I have been spending most time working on my thesis. It has been actually very enjoyable, for the most part. There have been some days where it has been somewhat painful. The quick update is that it is going well and that I still hope to submit very soon. As expected, there are many experiments, and tasks, and analysis that I would like to expand into. But I’m going to have to leave it for later. As Inman keeps reminding me, there is no such thing as a finished thesis…

But this post is not really about the thesis. I wanted to mention my increasing interest in the economy as an evolving complex dynamical system. This interest is not entirely new for me. I first became involved in the computational study of economic processes modeled as dynamic systems of interacting agents when I was assisting Prof. Raul Jimenez back in Universidad Simon Bolivar. However, it was the book “The Origin of Wealth: Evolution, Complexity and the Radical Remaking of Economics” by Eric D. Beinhocker - as brought to my attention by Chrisantha - which has gotten me thinking more seriously about the area again.

Prof. Tesfatsion has a very useful online resource on the area. These are some of the interesting questions that she raises: “Why have particular observed regularities evolved and persisted despite the absence of top-down planning and control?” and “How can computational models be used to gain a better understanding of economic systems through a better understanding of their full range of potential behaviors over time (equilibria plus basins of attraction)?”

I have also been most interested with Friederich von Hayek’s and Adam Smith’s work for a while. In fact, I have been recommending many Venezuelans to read Hayek’s seminal “Road to Serfdom” for the last several months. These gentleman wondered about the self-organizing capabilities of decentralized market economies. This is still an unresolved concern. One which I find ever so necessary to resolve.

Perhaps what I find most interesting about computational economic models is the potential to introduce all of the tools from dynamical, complex, adaptive, evolutionary, embedded, enactive and other biologically-inspired systems trade, as Beinhocker points out in his book.

I’m particularly interested in `out of equilibrium’ economics. Traditional economic models have been based around homogeneous all-knowing agents in a discrete-time world. And most of the analysis has been applied to when the market settles down to its equilibrium. Brian Arthur and some other people have done a lot of interesting work with their Santa Fe Institute artificial stock market (SFI-ASM). But from what I have seen so far, there is still a lot of space for improvement. There is also a lot of space for  understanding these models using dynamical systems analysis.

That’s it for the moment on computational economics. But I would like to mention a couple of other side things before I disappear into my latex files. I have also been reading “On writing well: the classic guide to writing nonfiction” by William K. Zinsser. This book complements very well W. Strunk and E.B. White’s “The Elements of Style”, as the author suggests.

It’s only until you read something as well written as this book that you realise how awful most of us write. And I’m not talking merely about blogs and things online, I’m talking about many papers and books out there. Zinsser puts it this way: “The man or woman snoozing in a chair with a magazine or a book is a person who was being given too much unnecessary trouble by the writer”. On the contrary, every paragraph in this book is refreshing and it gives me more energy to keep reading the next.

Anyways, I do hope to improve my writing with it. What I like about this book the most is that he acknoledges that good writing is hard. “A clear sentence is no accident” is the way he puts it. There is a lot of emphasis on clarity, simplicity, brevity and humanity. He also stresses the importance of how the written text ’sounds’. Also the necessity of pruning, rewriting, reading aloud and rewriting over again, several times. All of these suggestions are obvious. But it’s worth being reminded about them often. He recommends reading White and Strunk’s book every year. I agree. I also think this is true for his book.

Well, as it turns out this post was about all sorts of things and nothing at the same time. So while I’m at it, why not tell you the one other thing, after the thesis, that has been taking up most of my time: planning for the future. That’s right. Short and medium term future is what’s at stake. A lot of brainstorming about concrete research projects that I would like to carry out, with whom and where. I think I know pretty well what I want. More on this later.

Journals checked regularly (in no particular order):

Behavioral Neuroscience
Journal of Experimental Biology
Journal of Neurophysiology
Journal of Neurobiology
Journal of Neuroscience
Trends in Cognitive Sciences
Current Opinion in Neurobiology
Robotics and Autonomous Systems
Neuron
Journal of Computational Neuroscience
Neural Computation
Adaptive Behavior
Artificial Life
PLoS Biology
PLoS Computational Biology
Biological Cybernetics
Nature
Nature Neuroscience
Nature Reviews Neuroscience

For all except the last four I’ve made the link such that if you introduce your Sussex username and password you can not only check the titles but also download the papers. For the last three (yes including Nature!!!) Sussex has no access (and I have to resource to my wife’s password for help!).

By regularly I mean I check the table of content of each of those Journals at least once a month for articles of interest. I dedicate at least half a day per week to browsing through the titles. From this I end up piling up at least 10 new papers to read, of which I end up actually reading only 2 or 3. Hope to improve on this with time. I would particularly like to keep an online record of those that I found interesting with a specific note or two.

Finally, for many of these journals you can give out your mail and they’ll automatically send you the new titles as they come out. I’ve stopped checking them this way because of the ‘passivity’. I ended up checking the titles of the paper when the mail arrived, which most likely are times when I am not 100% up to properly reading them. So I would end up just reading the mail to get it out of the way and never coming back to them. Whereas by actively going to their websites I know I check only when is most appropriate.

So, briefly I’ll see if I can mention at least titles and authors of papers I’ve read or would like to read this week (and do this regularly.. fingers crossed):

Systems level circuit model of C. elegans undulatory locomotion: mathematical modeling and molecular genetics
Jan Karbowski, Gary Schindelman, Christopher J. Cronin, Adeline Seah and Paul W. Sternberg

Evolving a Neural Model of Insect Path Integration
Thomas Haferlach, Jan Wessnitzer, Michael Mangan, and Barbara Webb

The neuronal dynamics underlying cognitive flexibility in set shifting tasks
Anja Stemme, Gustavo Deco and Astrid Busch

Role of Nitric Oxide in Classical Conditioning of Siphon Withdrawal in Aplysia
Igor Antonov, Thomas Ha, Irina Antonova, Leonid L. Moroz, and Robert D. Hawkins

Multiple Memory Traces for Olfactory Reward Learning in Drosophila
Andreas S. Thum, Arnim Jenett, Kei Ito, Martin Heisenberg, and Hiromu Tanimoto

Capitalizing on cortical plasticity: influence of physical activity on cognition and brain function
Arthur F. Kramer and Kirk I. Erickson

Programmable springs: Developing actuators with programmable compliance for autonomous robots
Bill Bigge and Inman R. Harvey

Autonomous and fast robot learning through motivation
M. Rodríguez, R. Iglesias, C.V. Regueiro, J. Correa and S. Barro

Chained learning architectures in a simple closed-loop behavioural context
Tomas Kulvicius, Bernd Porr and Florentin Wörgötter

Developmental learning for autonomous robots
M.H. Lee, Q. Meng and F. Chao

Sensory adaptation
Barry Wark, Brian Nils Lundstrom and Adrienne Fairhall

Homeostatic signaling: the positive side of negative feedback
Gina Turrigiano

Learning to hear: plasticity of auditory cortical processing
Johannes C. Dahmen and Andrew J. King

Consistent dynamics suggests tight regulation of biophysical parameters in a small network of bursting neurons
Attila Sz�cs, Allen I. Selverston

Please let me know if I’m missing certain Journals that you think might be relevant. Also let me know if you have an overall strategy that works for you.

Before I move on to my daily research routine I will first attempt to reflect on the conference. Hopefully this way I can reduce the chances of forgetting it ever happened. I won’t go into much depth but only some of the things I remember most clearly.

ECAL felt like an extended-family-of-the-CCNR week-long meeting. And I think that’s a good thing. The most exciting organisational differences between this ECAL and the previous one, as well as at least the two last Alifes, had to be the panel discussions at the end of each day. Although the discussions were not always insightful (see point towards the end on information theory and dynamical systems), they usually reflected the state of something that’s happening in the Alife community. Another good thing about this conference was the stronger congruence throughout each day’s theme as embodied by the keynotes, talks and posters presented in each.

There were several talks that I particularly enjoyed. Randall Beer’s and Janet Wile’s keynotes were the most exciting for me. I liked them the most because of the clearness of their motivations, the relevance of their scientific questions, the concreteness of the frameworks they propose, and the in-depth and systematic approach that they usually take, among other things. What I particularly liked about Randy’s was his outlook for future directions of research. I also found inspiring his emphasis on the idea that the use of dynamical systems analysis was not impossible to achieve, but on the contrary quite tractable, as long - of course - as education on the language and the tools were available to the community. I very much liked how Janet Wiles was so aware of her role as a supervisor of grad students. She kept bringing the topic of ‘approaches to grad students’ up any chance she had, unfortunately I felt most of the times it was glossed over by the rest and usually put to one side.

There were other good talks. I enjoyed Ezequiel’s keynote because of its exploratory nature and the effort to tie the sort of work that evolutionary robotics people do (and not very unlike mine) together with important philosophical strands. Even though Jun Tani and Takashi Ikegami didn’t give keynotes, from their interventions a similar (if not more exploratory still) approach was always present. This was also refreshing. Particularly, because they were so honest about mostly doing it because it was fun for them. Interestingly enough, although I didn’t get most of Brian Goodwin’s points, his way of addressing us was very inspiring too.

Although I’m not usually amused by engineering feats, I was genuinely impressed with the work of Rudolf Bannasch. Undoubtedly, I was better able to appreciate the extent of his contributions precisely because he made it so clear throughout his talk that his motivation was purely in engineering. This is not typical in Alife. What is more characteristic is that certain disguised-in-science-but-engineering-at-heart works leaves a lot of people confused and makes me in particular obsess throughout the duration of their exposition about which scientific question is the one we are tackling. Also, one usually hears about how understanding of biological organisms is going to impact how we as engineers design machines, but it is not everyday that you see biologically-inspired machines out there in the world. His talk made it seem otherwise which was great. In some respects, I guess Dario Floreano’s talk also helped give that feeling a little bit.

As usual, it is the workshops that stand out the most for me. Unfortunately they all happen in parallel on the same day, so you can only attend to one or two. I attended Rachel Wood’s (and others) ‘dynamics of development’ workshop. Among the participants were Linda Smith, Jane Wiles, Jun Tani, Luc Bertouhze, Ezequiel Di Paolo. Lots of time for discussions and comments. I was fortunate to have been given the chance to comment on Josh Bongard’s latest internal self-modeling robot work and how it might go beyond the metaphor to answer questions relevant to developmental psychologists. I took the opportunity to refresh skepticism about the usefulness of sense-model-plan-act approaches in Robotics when they are used as scientific tools. Overall, I was mostly surprised with the readiness of a good proportion of the participants - in particular people whose work is very much along the lines of a situated, embodied and dynamical systems perspective - to take for granted that we have (or eventually develop) internal models of ourselves that we can ‘use’ to simulate things in.

Worth echoing here are two points that Randy brought up during this workshop. The first is one we are all very familiar with. Basically being very aware of not confusing engineering and science. Particularly of not falling into the trap of going to the scientific meetings and talking about the engineering and viceversa. The second point worth mentioning is regarding the relevance of physical or simulated models. Although I was familiar with the discussion, I hadn’t seen it from the perspective that Randy pointed out until then. His point was that the use of physical robots need not be, by default, more assumptions free nor more realistic, nor better in any a priori way than simulations. He gave a good example of how sometimes simulations can be more biologically realistic than physical models, and how this depended on the proof of how the relevant biomechanical properties compared to the real organism being modeled and not simply on the physicality of the robot - as choices of materials, dimensions, etc. could be very much inappropriate. This is how I interpreted and recall those two points now anyways.

I also took part in the ‘dynamics of learning and neuromodulation’ workshop, of course. That went really really well. Lots of people turned up. In fact some people told me it was one of the busiest workshops there. There was lots of discussion too. Some of it was unfortunately spent clarifying the two different levels of defining learning: mechanistic and behavioral. I understand that it is something that takes a while to assimilate, but I would have thought by now (and in the context of that workshop) that everybody would have been aware of the difference. Some people would inevitable (no matter how many times we reminded them) kept slipping back into a ‘learning as mechanism’ perspective. When that wasn’t the case however, an interesting discussion of what was behavioral learning dominated the discussion - with particularly relevant insights coming from Randy, Anil Seth, Chrisantha and Seth Bullock. This was particularly relevant for me as most of the issues that were discussed are very relevant for my thesis.

There were many good talks and posters as well. But it will take me longer to realise which are relevant for me and which aren’t.

Lisboa was great of course. I’m sure I don’t need to say much there. Undoubtedly, Barrio Alto served as the secondary venue for the conference.

One of the panel discussions opened up a debate about information theory and dynamical systems theory which was unfortunately not too insightful (it has been followed in the conference blog). For two reasons mainly. First, most people seemed to equate dynamical systems theory with particular dynamical neural models and information theory with computation. This obviously leads to people talking across each other about a lot of senseless stuff. Several people pointed this out during the discussion but a few minutes later the discussion would slip into loaded notions of the terms. Second, because people would sometimes argue that one was ‘a better tool’ than the other. This doesn’t make sense, on his own anyway. Better at what? Both of them are tools that can be used to analyse dynamical (and non-dynamical) agent/environment systems. What I think some people may have meant is that there can be certain types of question that one tool will be able to answer better than the other (and of course, some questions which might be better answered by using both or neither tools). Dynamicists, as they are sometimes called, think that certain aspects of interactions (such as relative timing, morphologies, biomechanics, etc.) are important for what they understand as cognition. Therefore, dynamical systems tools are most of the times the more appropriate tool to address the sorts of questions that they have about their systems of interest. On the other hand, informationists (or however these people are called), have very different types of questions about their systems. This is sometimes because of the nature of the systems which they study (such as throwing a dice with clearly labeled sides and discrete events in time), but ultimately the type of system under study should not force one to study it with one tool or the other. It is their type of questions that are different. For example, they might be interested in how much mutual information an agent shares with its environment. It is questions of this nature that they think are relevant for their understanding of cognition, for which information theory is a mighty powerful tool. In summary, I don’t think there is a debate worth having about which is a better tool. Particularly, in the absence of the context of which question and which system the user of the tool is trying to answer. It is more interesting to debate which questions we are asking about our agent/environment systems and the tools will simply follow.

Finally, a couple of comments regarding the blog and wiki that were set up. Ideally they should have been arranged with some more anticipation. More importantly, however, is that they be made more general ‘artificial life community’ blogs/wikis and not just ECAL2007 ones (e.g. http://artificiallife.wordpress.com/ ?). That’s only a minor matter of changing domain name and title I guess. Perhaps it should be done for the wiki. On a different but related idea, would anybody (else besides me) find useful a user-submitted voted-on and commented-on paper repository in the form of an ‘artificial life community digg-style’ site? Just a thought.

ps. as the astute reader will have noticed (I always wanted to say that phrase) I am making an effort to not so easily refer to the brain or the mind as the place where things ‘happen’ when we ‘think/learn/remember’ things (e.g. the title of the post). I’m sure you will have found it utterly silly and downright annoying. I don’t blame you. But I think it should be relevant to have a situated, embodied and dynamical systems perspective not just in our research but throughout our lives, down to even our most meaningless day-to-day expressions. Although I understand they are not meant to be accurate, I reckon the accumulation of these phrases make it harder to turn cognition into a less GOFAI-oriented science. I’m sure, however, that for the larger proportion of the three people reading this blog it will not come as a surprise that their body is relevant to what they learn and remember.

The following is a follow-up to my transfer function post a couple of days ago. Two persons have suggested using a simpler non-monotonic function such as the Gaussian. I will incorporate results with that transfer function. Also, I will add one more category to my previous minimalistic categorizationof asymptotic dynamics: point attractors versus other dynamics. I am now including periodic orbits. Still very minimalistic.

Each point in the data bellow corresponds to generating 1000 CTRNNs and estimating whether the dynamics after 100 units of time (with 0.01 time-step) are: (1) point attractor (black), (2) periodic stable orbit (gray), or (3) something else (white).

CTRNNs are drawn at random from the same parameters as before, except that I have made the range of time-constants a bit smaller (to lessen the possibility of transients after 100 units of time) to [e^0,e^3]. Also changed the initial state of the activations of all neurons to randomly between [-10,10].

Experiments were run with circuits of size 2 to 20, and with three transfer functions: logistic, Gaussian, and tanh+sin. In the case of the Gaussian transfer function, the mean is always 0 while the standard deviation for each node is a random number between [1,3]. In the case of the f=a*tanh() + (1-a)sin() function a is a random number in [0,1] for each node in the circuit.

       

I will give some analysis later, I have to do a bunch of other stuff today first… sorry.

I will try to express here two worries that I have had dancing around in my head (and probably body too) for some time now, but which I had not been too explicitly aware of until relatively recently. These preoccupations have arisen from general conversations with people in CCNR-related environments and have occurred with more than one person in different contexts, but it is not aimed at any one person in particular.

While there is a general feeling of people getting tired of this 2-behaviours, 2-environment-types, “2-attractors”, dynamical systems analyses of some minimally cognitive tasks.. most of any such analysis is still in such an early period of its infancy, because of the difficulties in studying multiple timescale, transient, hybrid (discontinuous as well as continuous variables), and non-autonomous (from the situatedness) dynamical systems, that I cannot help but fall into somewhat of a state of despair. On the one hand, I’m thinking to myself that I need another 4 years to understand even such simplest of systems. On the other, I can sort of feel the pressure of others around me suggesting that these are either too simple or too boring or too well understood already, and most likely all of the above.

Similarly, while many around me feel as if, unless an algorithmic version of the strategy of an evolved agent can be extracted from prolonged sessions of observing it interacting with the environment, little has been learned about the system; I remain to be more interested in a geometric/topological understanding of the interaction - from which I can feel many people near me remain skeptical about, despite these people being (more or less) on the dynamical-systems-understanding-of-adaptive-behaviour side of things.

I guess one has to properly explain the motivation for tackling any or both of these issues as clearly as possible in order to be understood, avoid such trivial criticisms, and hopefully even make the feeling of pressure to ‘move on to the interesting stuff’ disappear.

What effect does the neural transfer function have on the ‘interestingness’ of circuit dynamics? What counts as ‘interesting’ dynamics? I will present here one very simple and very preliminary study that suggests this is worth looking further into.

In continuous-time recurrent neural networks (CTRNNs), the most common transfer function is the logistic. My impression is that the second most used would be the tangent hyperbolic.. ? However, there’s never been any substantial claim (at least that I know of) of any large and fundamental differences between these two. Indeed, there isn’t any justification (as far as I’m aware) to use anything different than the logistic function - which is arguably the most biologically natural. Furthermore, as has been pointed out to me by Lionel, in the case of the tanh, the change is merely a mapping. Thus, the differences are not, in theory, any.

Even if there are no theoretical differences, there may still be quite important practical differences. This is what this post is concerned with. In particular, given the same volume of parameter space, qualitatively different dynamics could be differently represented. This would make for a substantial difference, particularly for evolutionary robotics type methodologies. For example, it could be the case that the volume in parameter space that generates CTRNNs that have phase-portraits with only stable point attractor(s) when using the logistic transfer function is larger than when using the tanh. This could mean, that in practice, more ‘interesting’ dynamics could be obtained (keeping everything else the same) with the latter.

So, what could we mean by ‘interesting’ dynamics? There could be several layers of ‘interestingness’ which I won’t talk about now. Let’s focus instead in the most minimal form of ‘interestingness’. The simplest behaviour one can obtain in a dynamical system is the point attractor. For the experiment in this post, I will define ‘minimal interestingness’ as anything but a point attractor. More precisely, I will explore randomly chosen networks from the following range: weights [-10,10], bias [-10,10], and time-constants [e^0,e^5]. I will do this for different sized networks, N in [2, 20], and 4 different transfer functions which I will explain ahead.

Each randomly chosen network is integrated (only once) for 100 units of time using Euler integration with a 0.01 time-step. During the last 50 units of time, the change of all neurons in the circuit are added up. The idea is that if it has settled into a point attractor, this accumulated change will be very small (in practice around 10^-12), if, on the other hand it settles into anything else (e.g. limit cycle, chaotic attractor, etc.) it will register as a larger accumulated difference (usually greater than 10). Note that the point of this exercise is not to check whether the randomly chosen circuit has ANY point attractor, but rather the proportion of falling in one by chance - as opposed to falling into anything else. Thus, each randomly chosen circuit is integrated only once. At the start of each test the activation of the neurons are set to random between [0,1].

The four transfer functions tested are the following:
(1) f = 1 / (1 + e^-x)
(2) f = tanh()
(3) f = 0.75*tanh() + 0.25*sin()
(4) f = a*tanh() + (1-a)*sin() ; where a is a random number between [0,1] for each neuron in the circuit.

Each point in the figure represents the proportion of circuits that are ‘minimally interesting’ (as defined above) out of 500 randomly chosen circuits. The effect seems to be a big one… particularly between the monotonic transfer functions (1 and 2) and the non-monotonic ones (3 and 4). Although not as pronounced, there seems to be some difference between the logistic and the tanh(). This is very much unexpected. The difference between (3) and (4) is even less pronounced, if any. I suspect raising the level of what counts as ‘interesting’ will probably make the differences between these last two grow. This I speculate from what I can see merely from eye-balling example dynamics.

What do you think? Why is this happening? Do you think this is worth looking at in more depth?

Note: as you may know already, the idea for the non-monotonic transfer function comes originally from Ollie Bown’s work.

Arthur C. Clarke presents Fractals - The Colors of Infinity (1995)

Is it that obvious that if you like A.C.Clarke’s work you will like dynamical systems and chaos? I wasn’t aware of the connection, but there must be quite a strong underlying one… Which explains why Lilia complains (and eventually falls asleep) every time I want to watch 2001: A Space Odyssey again.

Anyways, this documentary is a bit old : ) but still very much worth watching.

Quick note before I begin: it just so happens that as I wrote this post the disk on my G5 died. I don’t think I have lost anything major, as most of it is backed up. Some of the most recent pictures that I have taken may have gone, because I had failed to backup those in some time (a couple of months maybe). I am re-backing up what I have to a third disk to avoid having the just one copy that I have at this instant, and will seriously consider buying another disk to have more backups. On to the original post!

§0 There is little point in making up further excuses - all I have time for these days is making this sporadic updates to the blog after increasingly large periods of absence. As in previous posts, I’d like to recall what I have been up to lately and what the plans are - mostly for my own reference in two months from now when I start worrying about not having done enough.

§1 So first of all, I’m glad to be very involved in this upcoming ECAL, which increases in its promise to be quite exciting (e.g. the format, the organisation, the keynote speakers, the one-track session, the workshops and associated events, and of course, Lisbon). Here are some of the things I have become involved in.

§1.1 I had the honour of participating as part of the programme committee in the paper-reviewing process. This is one of the best research-related learning experiences. I have mentioned this previously in this blog. Even though the quality of the papers in my lot was rather poor, the experience was still a fruitful one. Attempting to get to the motivations of the contributions and be constructive as to how to meet the established claims, is something that I must practice more often, as it is all too easy to simply throw the towel and discard from merely pointing out the flaws. The obvious benefit of this practice is that one becomes increasingly aware of the need to step into the reviewer’s shoes (or any reader’s shoes for that matter) when writing.

§1.2 Which brings me to my second point… I submitted a paper which was accepted for a talk. The work follows on directly from the things I have been working on for the last two years: it deals with the analysis of a situated agent evolved to perform an associative learning task requiring re-learning. This work compliments well similar work and most importantly (which is the reason that I put all of the effort in) fills an important gap in my thesis.

§1.3 Even more exciting still have been the collaborations on two other papers that were also accepted.

§1.3.1 One of the collaborations arose from conversations about the meaning of autonomy with Tom and Nathaniel following from Life & Mind seminars. Our contribution points out two different dimensions in which autonomy should be approached: constitutive and behavioural. Pointing out that most progress in the artificial life sciences has been achieved towards the behavioural side of it, and less so on the constitutive aspects. We also point out the serious limitation of methodologies that assume the unit of agency a priori (such as evolutionary robotics) in advancing any further along the constitutive dimension.

§1.3.2 The other collaboration arose from discussions with Peter about his work, which is closely related to my own. The contribution explores situated agents evolved to learn about their sensori-motor configuration. The idea of the work is to provide a existence proof as well as to analyse successfully evolved systems that weren’t given a priori parameter-changing mechanisms for a variation of the visual inversion task. The work differs from previous work and my own in that what is being learned is not a feature of the environment, but a feature of the agent’s body.

§1.4 The workshop Eldan and I are organising is going well. We received some submissions, but not as many as we were hoping for. There are some plans to possibly merge with Andy’s workshop on Neuromodulation, given the relatedness of the topics. I’ll update on this soon.

§1.5 Finally, as regards ECAL, I’m also really looking forward to the associated-event / workshop on “Dynamical Approaches to Development” being organised by Rachel Wood and others, for which I was honoured to have been asked to participate as a commentator.

§2 On a different note, I have been picking up on my reading. I have recently finished reading James Gleick’s “Chaos: making a new science” and Eric Kandel’s “In search for memory”. Also read Charles Dicken’s “Great Expectations” (which I had been meaning to do since I was about 14 - but I think my English hadn’t been up to it until quite some time ago). Currently reading Alva Noe’s “Action in perception”. Have also been reading bits and pieces from Maggie Boden’s wonderful and relatively new book (which I really want to get but is too expensive!): “Mind as machine”. There are at least 10 more on the ‘hot’ queue awaiting..

§3 On the more administrative side of things, I have also been involved in a couple of projects.

§3.1 I have been taking a slightly more central role in the organising the Life and Mind seminars this summer term given that Tom is away in Sweden. Although very exciting it is such a time-consuming task. Unfortunately, I am most likely not going to be as involved from now on, for all the obvious reasons.

§3.2 I’m also very excited that Ezequiel has given me the opportunity to suggest, put on offer, and now that it has been taken up, co-supervise a thesis project for the EASy masters course. This is exciting work on the analysis of the dynamics of slight (and hopefully interesting) variations (mainly to the transfer function) to small (one and two coupled nodes) continuous-time recurrent neural networks.

§3.3 More in general, I reckon having moved to the Informatics building since I arrived from Indiana has been very beneficial because of increased interactions with people whose line of work I am interested in. Being next door to the EASy master’s lab has meant that some EASy students come and chat with me about their projects, I find this extremely interesting. I also run into people like: Anil Seth, Adrian Thompson, Thomas Nowotny, Phil Husbands, Mike Beaton, Ezequiel and Inman much more often. This is great too.

§4 That covers mostly what I have been up to for some time. What I’m getting busy with now is:

§4.1 My third and last annual review, for which I hope this post will serve as an initial step in getting that done.

§4.2 Generating a full-fleshed grant proposal, following from an accepted pre-proposal. More on this later, hopefully.

§4.3 Marking NSAI programming projects. Not much to say here. I think I would be slightly more enthusiastic if I had not my thesis to write. More generally as regards the teaching of the seminars for NSAI this last summer term, what happened to attendance!?? and how worried should I get about it? I don’t feel like I did such an awful job - I brought as much excitement as I generally assign to the topics covered, which is a lot! I encouraged them to discuss as much as possible. The class was on the early side of things, at least for students in England: 9am (if they only knew I used to get taught mathematics and physics at 7.30am in college in Venezuela on two hours lectures). When I asked the students and some colleagues of mine, most would say that this was the reason.. but I’m not convinced. I would like to hear honest feedback from my students, I will ask around if a form can be sent around for it - to see what went wrong.

§5 The important thing ahead is thesis writing - which I am now more anxious than ever to dedicate my full attention to.

§6 One thing I hope to do more of, which does not reflect at all in what I have been doing, is increasing my interactions with the biologists. I had the chance to meet with some of them working on learning and memory in the pond snail Lymnaea stagnalis the other day regarding the grant proposal that we are putting together, and it dawned on me the difficulty of crossing the gap between the two fields. Although extremely daunting, I hope to overcome this gap in the following years of my career in a way that doesn’t entail me ending up as the “computer scientist that’s programming for the biologists” configuration - which is what seems to happen very often. I want the high levels of abstraction, the enactive, evolutionary, and dynamical systems approach to feed into work in learning and memory in Biology, without having to model every detail of two particular cells, for example.

§§ On a final note (and although this should be a research-mostly blog), I can’t help to mention that I have been extremely worried about my home country lately. The direction it has been taken towards during the last 9 years has been, in my opinion, an extremely inappropriate one. But what has happened during these last months has just been absolutely unacceptable. This has nothing to do with left, right, up or down political positions; and everything to do with one men seeking full control of all powers. Venezuela has fallen into the depths of a totalitarian regime and this is no secret: if you happen to like his line of thinking, great; if you don’t, then you must leave. I won’t go into it in any detail here because I fear the few readers that might be interested in the rest of my blog will simply not care. What I will mention is what is most frustrating for me. First, that I don’t know what I can do to make the situation better - I go absolutely blank when I try to think of things to do. The other thing is that I would be much happier dedicating my full attention to the things that interest me (my scientific research) and not the political sanity of my country (which is every day less mine!).

This post is all over the place: from the technicalities of hard disk failure, through paper-writing, paper-reviewing and teacher-assisting, all the way up to political nonsense. There it is.

ps. many many thanks to our mac administrator Christian for all his excellent support in the disk situation, as usual.

ps2. I didn’t manage to make space in my ECAL paper for the acknowledgments… very cheeky I know. So,

Acknowledgments. I would like to thank Peter Fine for proof reading and making suggestions to improve the English of the last version. If it were not for him (and Inman of course) the paper would read more like this blog! Also thanks to Hiroyuki Iizuka for words of encouragement about the value of the contribution when in doubt.

Last Call for Participation
Evolution and Dynamics of Learning Behavior Workshop
to be held as part of ECAL 2007

The idea of this workshop will be to discuss exciting new directions
and developments in the understanding of the mechanisms underlying
learning behavior and in the environmental conditions required for it
to evolve.

Two important announcements:
** Extension of deadline to submit contributions for Wednesday 23rd
of this month.
** Prof. Randall Beer will be participating in our workshop with a
keynote talk.

For more information about the workshop please visit:
http://www.cogs.susx.ac.uk/ccnr/edl07/

For more information about the conference visit:
http://www.ecal2007.org/

Organisers,
Eldan Goldenberg
Eduardo Izquierdo

It is so sad that I have been too busy working to update my blog. Sad because keeping the notebook updated helps me stay focus on the bigger picture. Here’s a brief update on what I have been up to.

I have been mostly working on what I think will be the 5th and last experimental chapter of my thesis, a subset of which I am planning to submit to the upcoming ECAL conference with deadline a couple of weeks away (9th of April). The work is on the evolution, and more importantly for me the analysis, of an agent that can learn to associate food with temperature in a 2D environment during its lifetime, while overcoming the difficulties encountered by previous work (Yamauchi, Beer, Tuci, Blynel, Floreano, Phattanarasri, and Chrisantha). I’m particularly interested in attempting to understand the agent’s learning behavior in the language of animal learning theory (is the agent doing classical or instrumental conditioning?), as well as the ‘memory trace’ in the internal dynamics.

Fortunately, I have managed to succesfully evolve small circuits for the task (much smaller than all previous attempts in the literature) even though many aspects of the tasks are more complex: they have to be able to remember for several re-tests and be able to re-learn different environments during their lifetime. The smallness of the circuit (4 nodes) has encouraged its in-depth dynamical systems analysis (as opposed to the typical statistical measures, correlation and ablation studies).

I’m still hard at work analysing the agent and writing it up, but I will have a draft to share with whoever wants to read it fairly soon.

I have also been collaborating with Nathaniel and Tom (colleagues from the CCNR) on a review paper on the notion of autonomy in the cognitive sciences for the same conference. There is a lot of material already there, it’s a matter mostly of narrowing it down and making it as concise as possible. We have been meeting on and off for the last 3 months, that has been really useful and interesting. I would definitely like to engage in more collaborations of that sort.

I’m also getting my presentation ready for the IEEE conference in Hawaii, and that’s even closer! I leave on the 3oth of this month. Still need to work on it a lot more.

Will be sending our first call for papers for the workshop that Eldan and I are organising in Portugal next week. It’s very exciting. I think there is a lot of space for really interesting discussions, new directions and collaborations to take place from that workshop.

There are a couple of other things, also important and interesting, which I won’t go into now. Laters.