Modelling Learning as Modelling

Economists tend to represent learning as a procedure for estimating the parameters of the "correct" econometric model. We extend this approach by assuming that agents specify as well as estimate models. Learning thus takes the form of a dynamic process of developing models using an internal language of representation where expectations are formed by forecasting with the best current model. This introduces a distinction between the form and content of the internal models which is particularly relevant for boundedly rational agents. We propose a framework for such model development which use a combination of measures: the error with respect to past data, the complexity of the model, the cost of finding the model and a measure of the model's specificity The agent has to make various trade-offs between them. A utility learning agent is given as an example

From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness

Challenges in Modelling Social Conflicts: Grappling with Polysemy

This discussion paper originates from the preceding annual workshop of the Special Interest Group on Social Conflict and Social Simulation (SIG-SCSS) of the ESSA. The workshop especially focused on the need to identify and examine challenges to modeling social conflicts. It turned out that the polysemous nature of social conflicts makes it very difficult to get a grasp of their complexity. In order to deal with this complexity, various dimensions have to be taken into consideration, beginning with the question of how to identify a conflict in the first place. Other dimensions include the relation of conflict and rationality and how to include non-rational factors into conflict models. This involves a conception of organized action. Finally, guiding principles for model development are being discussed. We would like to invite readers of the Journal of Artificial Societies and Social Simulation to 'sow the seeds' of this debate.Social Conflicts, Conflict Models, Modelling Challenges, Polysemy, Rationality, Emotions

Behavioural Economics: Classical and Modern

In this paper, the origins and development of behavioural economics, beginning with the pioneering works of Herbert Simon (1953) and Ward Edwards (1954), is traced, described and (critically) discussed, in some detail. Two kinds of behavioural economics – classical and modern – are attributed, respectively, to the two pioneers. The mathematical foundations of classical behavioural economics is identified, largely, to be in the theory of computation and computational complexity; the corresponding mathematical basis for modern behavioural economics is, on the other hand, claimed to be a notion of subjective probability (at least at its origins in the works of Ward Edwards). The economic theories of behavior, challenging various aspects of 'orthodox' theory, were decisively influenced by these two mathematical underpinnings of the two theoriesClassical Behavioural Economics, Modern Behavioural Economics, Subjective Probability, Model of Computation, Computational Complexity. Subjective Expected Utility

Tracing the Biological Roots of Knowledge

The essay is a critical review of three possible approaches in the theory of knowledge while tracing the biological roots of knowledge: empiricist, rationalist and developmentalist approaches. Piaget's genetic epistemology, a developmentalist approach, is one of the first comprehensive treatments on the question of tracing biological roots of knowledge. This developmental approach is currently opposed, without questioning the biological roots of knowledge, by the more popular rationalist approach, championed by Chomsky. Developmental approaches are generally coherent with cybernetic models, of which the theory of autopoiesis proposed by Maturana and Varela made a significant theoretical move in proposing an intimate connection between metabolism and knowledge. Modular architecture is currently considered more or less an undisputable model for both biology as well as cognitive science. By suggesting that modulation of modules is possible by motor coordination, a proposal is made to account for higher forms of conscious cognition within the four distinguishable layers of the human mind. Towards the end, the problem of life and cognition is discussed in the context of the evolution of complex cognitive systems, suggesting the unique access of phylogeny during the ontogeny of human beings as a very special case, and how the problem cannot be dealt with independent of the evolution of coding systems in nature

From Economic Activity to Understanding Spaces

This paper constructs the probability space underlying the random variable of any time dependent econometric specification. The construction links concrete economic activity, both perceived and recorded, and econometric formulations. Furthermore, it is argued that the probability events belonging to this space are forms of understanding economic activity held by each agent. The model establishes two aspects of any econometric formulation. Mainly, that learning must be unique between any two ticks of the clock and that not all forms of understandings can indeed become events in the random variable’s probability space. Finally, a model of the dependencies based on agent-based understandings, and evolution thereof, is presented as well.Knowledge intuitions probability

The *subjectivity* of subjective experience - A representationalist analysis of the first-person perspective

This is a brief and accessible English summary of the "Self-model Theory of Subjectivity" (SMT), which is only available as German book in this archive. It introduces two new theoretical entities, the "phenomenal self-model" (PSM) and the "phenomenal model of the intentionality-relation" PMIR. A representationalist analysis of the phenomenal first-person persepctive is offered. This is a revised version, including two pictures