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Ben Meadows

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2 papers
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2

ICAPS Conference 2017 Conference Paper

What Can I Not Do? Towards an Architecture for Reasoning about and Learning Affordances

  • Mohan Sridharan
  • Ben Meadows
  • Rocío Gómez

This paper describes an architecture for an agent to learn and reason about affordances. In this architecture, Answer Set Prolog, a declarative language, is used to represent and reason with incomplete domain knowledge that includes a representation of affordances as relations defined jointly over objects and actions. Reinforcement learning and decision-tree induction based on this relational representation and observations of action outcomes are used to interactively and cumulatively (a) acquire knowledge of affordances of specific objects being operated upon by specific agents; and (b) generalize from these specific learned instances. The capabilities of this architecture are illustrated and evaluated in two simulated domains, a variant of the classic Blocks World domain, and a robot assisting humans in an office environment.

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AAAI Conference 2014 Conference Paper

Social Planning: Achieving Goals by Altering Others’ Mental States

  • Chris Pearce
  • Ben Meadows
  • Pat Langley
  • Mike Barley

In this paper, we discuss a computational approach to the cognitive task of social planning. First, we specify a class of planning problems that involve an agent who attempts to achieve its goals by altering other agents’ mental states. Next, we describe SFPS, a flexible problem solver that generates social plans of this sort, including ones that include deception and reasoning about other agents’ beliefs. We report the results for experiments on social scenarios that involve different levels of sophistication and that demonstrate both SFPS’s capabilities and the sources of its power. Finally, we discuss how our approach to social planning has been informed by earlier work in the area and propose directions for additional research on the topic.

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