223,332 research outputs found

    A computer scientist looks at game theory

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    I consider issues in distributed computation that should be of relevance to game theory. In particular, I focus on (a) representing knowledge and uncertainty, (b) dealing with failures, and (c) specification of mechanisms.Comment: To appear, Games and Economic Behavior. JEL classification numbers: D80, D8

    Coordinated Multi-Agent Imitation Learning

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    We study the problem of imitation learning from demonstrations of multiple coordinating agents. One key challenge in this setting is that learning a good model of coordination can be difficult, since coordination is often implicit in the demonstrations and must be inferred as a latent variable. We propose a joint approach that simultaneously learns a latent coordination model along with the individual policies. In particular, our method integrates unsupervised structure learning with conventional imitation learning. We illustrate the power of our approach on a difficult problem of learning multiple policies for fine-grained behavior modeling in team sports, where different players occupy different roles in the coordinated team strategy. We show that having a coordination model to infer the roles of players yields substantially improved imitation loss compared to conventional baselines.Comment: International Conference on Machine Learning 201

    Analysing the behaviour of robot teams through relational sequential pattern mining

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    This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

    Egocentric Spatial Representation in Action and Perception

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    Neuropsychological findings used to motivate the “two visual systems” hypothesis have been taken to endanger a pair of widely accepted claims about spatial representation in visual experience. The first is the claim that visual experience represents 3-D space around the perceiver using an egocentric frame of reference. The second is the claim that there is a constitutive link between the spatial contents of visual experience and the perceiver’s bodily actions. In this paper, I carefully assess three main sources of evidence for the two visual systems hypothesis and argue that the best interpretation of the evidence is in fact consistent with both claims. I conclude with some brief remarks on the relation between visual consciousness and rational agency

    Civil Legal Assistance for Low-Income Persons: Looking Back and Looking Forward

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    This Article discusses the importance of legal aid and the services it provides to low-income persons. The Article also addresses the need for further change. It advocates for the development of a stronger base of public support at the local level. It also calls for an integrated, comprehensive statewide system to ensure that access is available to all those who need relief
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