Towards Designing Artificial Universes for Artificial Agents under Interaction Closure

We are interested in designing artificial universes for artificial agents. We view artificial agents as networks of highlevel processes on top of of a low-level detailed-description system. We require that the high-level processes have some intrinsic explanatory power and we introduce an extension of informational closure namely interaction closure to capture this. Then we derive a method to design artificial universes in the form of finite Markov chains which exhibit high-level processes that satisfy the property of interaction closure. We also investigate control or information transfer which we see as an building block for networks representing artificial agent

Statistical physics and practical training of soft-committee machines

Equilibrium states of large layered neural networks with differentiable activation function and a single, linear output unit are investigated using the replica formalism. The quenched free energy of a student network with a very large number of hidden units learning a rule of perfectly matching complexity is calculated analytically. The system undergoes a first order phase transition from unspecialized to specialized student configurations at a critical size of the training set. Computer simulations of learning by stochastic gradient descent from a fixed training set demonstrate that the equilibrium results describe quantitatively the plateau states which occur in practical training procedures at sufficiently small but finite learning rates.Comment: 11 pages, 4 figure

Apparent actions and apparent goal-directedness

Daniel Polani, Martin Biehl, ‘Apparent actions and apparent goal-directedness’, paper presented at the 13th European Conference on Artificial Life (ECAL 2015), York, UK, 20-24 July, 2015.In human history countless phenomena have been (wrongly) attributed to agents. For instance, now science believes there are no gods (agents) of lightning, thunder and wind behind the associated phenomena. In physics (assuming quantum decoherence) the universe is modelled as a state space with a dynamical law that determines everything that happens within it. This however, is incompatible with most notions of agency (cf. Barandiaran et al., 2009) which require actions: For an agent candidate to have actions it must be able to “make something happen” as opposed to only “have things happen to it”. Here we ask which single sequences of partial observations may appear to contain agency to a passive observer who has its own memory. For this we define measures of apparent actions and apparent goal-directedness. Goal-directedness is another feature commonly attributed to agents. We here ignore whatever causes the appearances and the concept of individuality of agents.Peer reviewedFinal Accepted Versio

Specific and complete local integration of patterns in Bayesian networks

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The Version of Record, Daniel Polani, et al, Entropy, Vol. 19 (5), Article number 230, published 18 May 2017, is available online at doi:10.3390/e19050230.We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the ι-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.Peer reviewedFinal Published versio

Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems

© 2016 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0 - https://creativecommons.org/licenses/by/4.0/) license.We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dynamical systems model of the biosphere we argue that the metabolism, motility, and the concept of counterfactual variation should be compatible with any agent representation in dynamical systems. We then propose an information-theoretic notion of integrated spatiotemporal patterns which we believe can serve as the basic building block of an agent definition. We argue that these patterns are capable of solving the problems mentioned before. We also test this in some preliminary experiments

Flat (001) surfaces of II-VI semiconductors: A lattice gas model

We present a two-dimensional lattice gas with anisotropic interactions which model the known properties of the surface reconstructions of CdTe and ZnSe. In constrast to an earlier publication [12], the formation of anion dimers is considered. This alters the behaviour of the model considerably. We determine the phase diagram of this model by means of transfer matrix calculations and Monte Carlo simulations. We find qualitative agreement with the results of various experimental investigations.Comment: 17 pages, 5 figures. See http://theorie.physik.uni-wuerzburg.de/~ahr/ for related publication

A technical critique of the free energy principle as presented in "Life as we know it" and related works

We summarize the argument in Friston (2013, https://doi.org/10.1098/rsif.2013.0475) and highlight some technical errors. We also discuss how these errors affect the very similar Friston (2014, https://doi.org/10.1109/JPROC.2014.2306251) and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, https://royalsocietypublishing.org/doi/full/10.1098/rsta.2019.0159). The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanket will appear to engage in Bayesian inference. In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets which turns out not to be generally correct. We prove the non-equivalence with a counterexample that exhibits a Markov blanket but does not satisfy the rewritten equations. Our counterexample also invalidates the corresponding (but more general) rewritten equations in the more recent Friston (2019). The second error concerns the Free Energy Lemma itself, which we prove, by counterexample, to be wrong in general. The third is the claim that the Free Energy Lemma, when it does hold, implies equality of variational density and ergodic conditional density. The interpretation in terms of Bayesian inference hinges on this point, and we hence conclude that it is unjustified. Additionally, we highlight that the definitions of the Markov blanket in Friston (2013) and Parr et al. (2019) are not equivalent and that the assumptions in Parr et al. (2019) may be too strong to allow for meaningful interpretation.Comment: 27 pages, 1 figure. This replacement reflects some feedback by Karl Friston and Thomas Parr. It also contains stronger results than the previous version. Martin Biehl and Felix A. Pollock contributed equally to this wor