Learning Nested Agent Models in an Information Economy
We present our approach to the problem of how an agent, within an economic Multi-Agent System, can determine when it
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Scalability of Genetic Programming and Probabilistic Incremental Program Evolution
This paper discusses scalability of standard genetic programming (GP) and the probabilistic incremental program evolution (PIPE). To investigate the need
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How to Shift Bias: Lessons from the Baldwin Effect
An inductive learning algorithm takes a set of data as input and generates a hypothesis as output. A set of
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Neural Architectures for Robot Intelligence
We argue that the direct experimental approaches to elucidate the architecture of higher brains may benefit from insights gained from
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