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Exploration and Exploitation in an Artificial Experimenter

Record type: Conference or Workshop Item (Paper)

An artificial experimenter is a computational implementation of the decision making processes a laboratory experimenter will make. Artificial experimenter's analyse the available data, propose hypotheses to represent the behaviours investigated and design experiments to evaluate or improve those hypotheses. In doing so they perform active discovery. A key problem faced is deciding when to perform experiments that exploit the information held within the current hypotheses to evaluate them and when to perform experiments that explore the parameter space to discover features of the behaviour being investigated not yet identified. As resources in physical experimentation are extremely limited, addressing this trade-off is critical to obtaining a representative model of the system under investigation. To achieve this, a Bayesian notion of surprise has been used to effectively manage the transition between exploration and exploitation in simulated and physical experimental trials.

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Citation

Lovell, Chris, Zauner, Klaus-Peter and Gunn, Steve (2011) Exploration and Exploitation in an Artificial Experimenter At ICML Workshop on On-line Trading of Exploration and Exploitation 2.

More information

Published date: 25 May 2011
Venue - Dates: ICML Workshop on On-line Trading of Exploration and Exploitation 2, 2011-05-25
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 272579
URI: http://eprints.soton.ac.uk/id/eprint/272579
PURE UUID: 41005c6a-60df-4c4c-890d-5bb2824167e9

Catalogue record

Date deposited: 18 Jul 2011 12:40
Last modified: 18 Jul 2017 06:22

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Contributors

Author: Chris Lovell
Author: Klaus-Peter Zauner
Author: Steve Gunn

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