Eduardo Izquierdo
Research Interests
My primary research interest is in understanding how coordinated behavior arises from the dynamical
interaction of an animal's nervous system, its body and its
environment. Toward this end, I work on the evolution and analysis of dynamical "nervous systems" for model agents, neuromechanical modeling of animals, biologically-inspired robotics, and dynamical systems approaches to behavior and cognition. More generally, I am interested in computational and theoretical biology, including models of metabolism, gene regulation and development. I also have a longstanding interest in the design and implementation of dynamic programming languages and their programming environments.
Selected Recent Publications
(Complete publications here)
Williams, P.L. and Beer, R.D. (submitted). Generalized measures of information transfer. [arXiv preprint 1102.1507]
Williams, P.L. and Beer, R.D. (submitted). Decomposing multivariate information.
Flecker, B., Alford, W., Beggs, J.M., Williams, P.L. and Beer, R.D. (2011). Partial information decomposition as a spatiotemporal filter. Chaos 21:037104.
Beer, R.D. (2011). Computer evolution of chemotaxis in model nematodes. Brain, Behavior and Evolution 77:1-2.
Beer, R.D. and Daniels, B.C. (2010). Saturation probabilities of continuous-time sigmoidal networks. The supplemental Mathematica notebook can be downloaded here. arXiv preprint 1010.1714.
Williams, P.L. and Beer, R.D. (2010). Information dynamics of evolved agents. In S. Doncieux, B. Girard, A. Guillot, J. Hallam, J.-A. Meyer and J-B. Mouret (Eds.), From Animals to Animats 11: Proceedings of the 11th International Conference on Simulation of Adaptive Behavior (pp. 38-49). Springer. [Winner of a Best Paper Award]
Kadihasanoglu, D., Beer, R.D., and Bingham, G.P. (2010). The dependence of braking strategies on optical variables in an evolved model of visually-guided braking. In S. Doncieux, B. Girard, A. Guillot, J. Hallam, J.-A. Meyer and J-B. Mouret (Eds.), From Animals to Animats 11: Proceedings of the 11th International Conference on Simulation of Adaptive Behavior (pp. 555-564). Springer.
Beer, R.D. (in press). Dynamical analysis of evolved agents: A primer. To appear in P. Vargas, E. Di Paolo, I. Harvey and P. Husbands (Eds.) The Horizons for Evolutionary Robotics.
Beer, R.D. (in press). Dynamical systems and embedded cognition. To appear in K.
Frankish and W. Ramsey (Eds.), The Cambridge Handbook of Artificial Intelligence.
Cambridge University Press.
Williams, P.L. and Beer, R.D. (2010). Nonnegative decomposition of multivariate information. arXiv preprint 1004.2515.
Beer, R.D. (2010). Fitness space structure of a neuromechanical system. Adaptive Behavior 18:93-115.
Software
Dynamica
A Mathematica package for the analysis of smooth dynamical systems. Dynamica includes tools for computing and displaying the vector fields, trajectories, flows, phase portraits, bifurcation diagrams and parameter charts of dynamical systems described by sets of ordinary differential equations.
Version 1.0.5 - 12/6/11 (Release Notes)
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Evolutionary Agents
C++ software to support the evolution of model agents controlled by continuous-time recurrent neural networks.
Version 1.1.2 - 6/16/09 (Release Notes)
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Cocoa Bridge
The purpose of CocoaBridge is to make Apple's Cocoa framework as easy as possible to use
from ClosureCL, in order to support GUI application and development
environment activities. CocoaBridge provides Lisp-like syntax and
naming conventions for ObjC object creation and message sending, with
automatic type processing and compile-time checking of message
sends. It also provides some convenience facilities for working with
Cocoa. This software is now distributed with ClosureCL. Documentation of the ongoing ObjC/CLOS integration efforts in ClosureCL can be found at The Objective-C Bridge.
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FPC-PPC (Version 0.21)
A floating-point compiler for MCL and ClosureCL. This compiles Lisp double-float expressions directly into PPC assembly language, producing code that is usually faster and that allocates much less memory than the Lisp compiler.
(Code | Documentation)
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Basic Lisp (Version 1.1)
This one is just for fun. When I first learned Lisp in 1981, I did so by reading Winston and Horn's book and writing my own Lisp interpreter. The interpreter was written in Basic on the only system I had access to at the time: a TRS-80 Model I. This interpreter eventually ended up as part of a series of three articles on Lisp that I wrote for 80 Micro, a TRS-80 hobbyist magazine. The first part of the series, which contains the source code for the interpreter itself, is included here. Note that the listing has all optional spaces removed so that I could fit both the interpreter and 1100 (!) cons cells into 16K of memory.
(Part 1)
