Dr. Mark Humphrys

School of Computing. Dublin City University.

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Mark Humphrys - Research - PhD - Appendix G - References



References


Aylett, 1995
Aylett, Ruth (1995), Multi-Agent Planning: Modelling Execution Agents, Papers of the 14th Workshop of the UK Planning and Scheduling Special Interest Group.

Baum, 1996
Baum, Eric B. (1996), Toward a Model of Mind as a Laissez-Faire Economy of Idiots, Proceedings of the Thirteenth International Conference on Machine Learning.

Blumberg, 1994
Blumberg, Bruce (1994), Action-Selection in Hamsterdam: Lessons from Ethology, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

Brooks, 1986
Brooks, Rodney A. (1986), A robust layered control system for a mobile robot, IEEE Journal of Robotics and Automation 2:14-23.

Brooks, 1991
Brooks, Rodney A. (1991), Intelligence without Representation, Artificial Intelligence 47:139-160.

Brooks, 1991a
Brooks, Rodney A. (1991), Intelligence without Reason, Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI-91).

Brooks, 1994
Brooks, Rodney A. (1994), Coherent Behavior from Many Adaptive Processes, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

Charpillet et al., 1996
Charpillet, Francois; Chevrier, Vincent; Foisel, Remy and Haton, Jean-Paul (1996), Organizing a Society of Softbots for World Wide Web Applications, workshop on Artificial Intelligence-based tools to help W3 users, Fifth International World Wide Web Conference.

Clocksin and Moore, 1989
Clocksin, William F. and Moore, Andrew W. (1989), Experiments in Adaptive State-Space Robotics, Proceedings of the 7th Conference of the Society for Artificial Intelligence and Simulation of Behaviour (AISB-89).

Dennett, 1978
Dennett, Daniel C. (1978), Why not the whole iguana?, Behavioral and Brain Sciences 1:103-104.

Dennett, 1991
Dennett, Daniel C. (1991), Consciousness Explained, Allen Lane, The Penguin Press.

Digney, 1996
Digney, Bruce L. (1996), Emergent Hierarchical Control Structures: Learning Reactive/Hierarchical Relationships in Reinforcement Environments, Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (SAB-96).

Edelman, 1989
Edelman, Gerald M. (1989), The Remembered Present: A Biological Theory of Consciousness, Basic Books.

Edelman, 1992
Edelman, Gerald M. (1992), Bright Air, Brilliant Fire: On the Matter of the Mind, Basic Books.

Grefenstette, 1992
Grefenstette, John J. (1992), The Evolution of Strategies for Multi-agent Environments, Adaptive Behavior 1:65-89.

Holland, 1975
Holland, John H. (1975), Adaptation in Natural and Artificial Systems, Ann Arbor, Univ. Michigan Press.

Humphrys, 1995
Humphrys, Mark (1995), W-learning: Competition among selfish Q-learners, technical report no.362, University of Cambridge, Computer Laboratory.

Humphrys, 1995a
Humphrys, Mark (1995), Towards self-organising Action Selection, Papers of the 14th Workshop of the UK Planning and Scheduling Special Interest Group.

Humphrys, 1996
Humphrys, Mark (1996), Action Selection in a hypothetical house robot: Using those RL numbers, Proceedings of the First International ICSC Symposia on Intelligent Industrial Automation (IIA-96) and Soft Computing (SOCO-96).

Humphrys, 1996a
Humphrys, Mark (1996), Action Selection methods using Reinforcement Learning, PhD thesis (first version), University of Cambridge, Computer Laboratory.

Jackson, 1987
Jackson, John V. (1987), Idea for a Mind, SIGART Newsletter, Number 101, July 1987.

Kaelbling, 1993
Kaelbling, Leslie Pack (1993), Learning in Embedded Systems, The MIT Press/Bradford Books.

Kaelbling, 1993a
Kaelbling, Leslie Pack (1993), Hierarchical Learning in Stochastic Domains, Proceedings of the Tenth International Conference on Machine Learning.

Kaelbling et al., 1996
Kaelbling, Leslie Pack; Littman, Michael L. and Moore, Andrew W. (1996), Reinforcement Learning: A Survey, Journal of Artificial Intelligence Research 4:237-285.

Karlsson, 1997
Karlsson, Jonas (1997), Learning to Solve Multiple Goals, PhD thesis, University of Rochester, Department of Computer Science.

Lin, 1992
Lin, Long-Ji (1992), Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching, Machine Learning 8:293-321.

Lin, 1993
Lin, Long-Ji (1993), Scaling up Reinforcement Learning for robot control, Proceedings of the Tenth International Conference on Machine Learning.

Maes, 1989
Maes, Pattie (1989), How To Do the Right Thing, Connection Science 1:291-323.

Maes, 1989a
Maes, Pattie (1989), The dynamics of action selection, Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-89).

Mataric, 1994
Mataric, Maja J. (1994), Learning to behave socially, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

McFarland, 1989
McFarland, David (1989), Problems of Animal Behaviour, Longman.

Metcalfe and Boggs, 1976
Metcalfe, Robert M. and Boggs, David R. (1976), Ethernet: Distributed Packet Switching for Local Computer Networks, Communications of the ACM 19:395-404.

Minsky, 1986
Minsky, Marvin (1986), The Society of Mind (and here), Simon and Schuster, New York.
See Notes on it by Michael Dawson.
Also some essays here and here.

Moore, 1990
Moore, Andrew W. (1990), Efficient Memory-based Learning for Robot Control, PhD thesis, University of Cambridge, Computer Laboratory.

Ono et al., 1996
Ono, Norihiko; Fukumoto, Kenji and Ikeda, Osamu (1996), Collective Behavior by Modular Reinforcement-Learning Animats, Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (SAB-96).

Ray, 1991
Ray, Thomas S. (1991), An Approach to the Synthesis of Life, Artificial Life II.

Ring, 1992
Ring, Mark (1992), Two Methods for Hierarchy Learning in Reinforcement Environments, Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB-92).

Rosenblatt, 1995
Rosenblatt, Julio K. (1995), DAMN: A Distributed Architecture for Mobile Navigation, Proceedings of the 1995 AAAI Spring Symposium on Lessons Learned from Implemented Software Architectures for Physical Agents.

Rosenblatt and Thorpe, 1995
Rosenblatt, Julio K. and Thorpe, Charles E. (1995), Combining Multiple Goals in a Behavior-Based Architecture, Proceedings of the 1995 International Conference on Intelligent Robots and Systems (IROS-95).

Ross, 1983
Ross, Sheldon M. (1983), Introduction to Stochastic Dynamic Programming, Academic Press, New York.

Rummery and Niranjan, 1994
Rummery, Gavin and Niranjan, Mahesan (1994), On-line Q-learning using Connectionist systems, technical report no.166, University of Cambridge, Engineering Department.

Sahota, 1994
Sahota, Michael K. (1994), Action Selection for Robots in Dynamic Environments through Inter-behaviour Bidding, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

Scheier and Pfeifer, 1995
Scheier, Christian and Pfeifer, Rolf (1995), Classification as Sensory-Motor Coordination, Proceedings of the 3rd European Conference on Artificial Life (ECAL-95).

Selfridge and Neisser, 1960
Selfridge, Oliver G. and Neisser, Ulric (1960), Pattern recognition by machine, Scientific American 203:60-68.

Singh, 1992
Singh, Satinder P. (1992), Transfer of Learning by Composing Solutions of Elemental Sequential Tasks, Machine Learning 8:323-339.

Singh et al., 1994
Singh, Satinder P.; Jaakkola, Tommi and Jordan, Michael I. (1994), Learning without state-estimation in Partially Observable Markovian Decision Processes, Proceedings of the Eleventh International Conference on Machine Learning.

Sporns, 1995
Sporns, Olaf (1995), personal communication.

Steels, 1994
Steels, Luc (1994), A case study in the Behavior-Oriented design of Autonomous Agents, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

Sutton, 1988
Sutton, Richard S. (1988), Learning to Predict by the Methods of Temporal Differences, Machine Learning 3:9-44.

Sutton, 1990
Sutton, Richard S. (1990), Integrated Architectures for Learning, Planning and Reacting Based on Approximating Dynamic Programming, Proceedings of the Seventh International Conference on Machine Learning.

Sutton, 1990a
Sutton, Richard S. (1990), Reinforcement Learning Architectures for Animats, Proceedings of the First International Conference on Simulation of Adaptive Behavior (SAB-90).

Tan, 1993
Tan, Ming (1993), Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents, Proceedings of the Tenth International Conference on Machine Learning.

Tesauro, 1992
Tesauro, Gerald (1992), Practical Issues in Temporal Difference Learning, Machine Learning 8:257-277.

Tham and Prager, 1994
Tham, Chen K. and Prager, Richard W. (1994), A modular Q-learning architecture for manipulator task decomposition, Proceedings of the Eleventh International Conference on Machine Learning.

Todd et al., 1994
Todd, Peter M.; Wilson, Stewart W.; Somayaji, Anil B. and Yanco, Holly A. (1994), The blind breeding the blind: Adaptive behavior without looking, Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94).

Tyrrell, 1993
Tyrrell, Toby (and here) (1993), Computational Mechanisms for Action Selection (and ftp), PhD thesis, University of Edinburgh, Centre for Cognitive Science.

Varian, 1993
Varian, Hal R. (1993), Intermediate Microeconomics, W.W.Norton and Co.

Watkins, 1989
Watkins, Christopher J.C.H. (1989), Learning from delayed rewards, PhD thesis, University of Cambridge, Psychology Department.

Watkins and Dayan, 1992
Watkins, Christopher J.C.H. and Dayan, Peter (1992), Technical Note: Q-Learning, Machine Learning 8:279-292.

Weir, 1984
Weir, Michael (1984), Goal-Directed Behaviour, Gordon and Breach.

Whitehead et al., 1993
Whitehead, Steven; Karlsson, Jonas and Tenenberg, Josh (1993), Learning Multiple Goal Behavior via Task Decomposition and Dynamic Policy Merging, in Connell and Mahadevan, eds., Robot Learning, Kluwer Academic Publishers.

Wilson, 1990
Wilson, Stewart W. (1990), The animat path to AI, Proceedings of the First International Conference on Simulation of Adaptive Behavior (SAB-90).

Wixson, 1991
Wixson, Lambert E. (1991), Scaling reinforcement learning techniques via modularity, Proceedings of the Eighth International Conference on Machine Learning.




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