A Developmental Organization for Robot Behavior

This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions of dynamic pattern theory in which behavior is an artifact of coupled dynamical systems with a number of controllable degrees of freedom. In our model, the events that delineate control decisions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential knowledge gathering and representation tasks and provide examples of the kind of developmental milestones that this approach has already produced in our lab

Alternative characterizations of Boston mechanism

Kojima and Ünver (2011) are the first to characterize the class of mechanisms coinciding with the Boston mechanism for some priority order. By mildly strengthening their central axiom, we are able to pin down the Boston mechanism outcome for every priority order. Our main result shows that a mechanism is outcome equivalent to the Boston mechanism at every priority if and only if it respects both preference rankings and priorities and satisfies individual rationality for schools. In environments where each student is acceptable to every school, respecting both preference rankings and priorities is enough to characterize the Boston mechanism

From conceptual probabilistic behavior to operational measurements.

Behavior; Measurement;

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

The Evolution of Reaction-diffusion Controllers for Minimally Cognitive Agents

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Bad Nature, Bad Nurture, and Testimony Regarding MAOA and SLC6A4 Genotyping in Murder Trials

Recent research—in which subjects were studied longitudinally from childhood until adulthood—has started to clarify how a child’s environment and genetic makeup interact to create a violent adolescent or adult. For example, male subjects who were born with a particular allele of the monoamine oxidase A gene and also were maltreated as children had a much greater likelihood of manifesting violent antisocial behavior as adolescents and adults. Also, individuals who were born with particular alleles of the serotonin transporter gene and also experienced multiple stressful life events were more likely to manifest serious depression and suicidality. This research raises the question of whether testimony regarding a defendant’s genotype, exposure to child maltreatment, and experience of unusual stress is appropriate to present during the guilt or penalty phases of criminal trials, especially when capital punishment is a consideration. The authors present their experience in genotyping criminal defendants and presenting genetic information at criminal trials

Talking Nets: A Multi-Agent Connectionist Approach to Communication and Trust between Individuals

A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents’ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Grice’s (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions