E. J. Collins

发表

Dynamic optimization in fluctuating environments

John M. McNamara, James N. Webb, E. J. Collins, 1995, Proceedings of the Royal Society of London. Series B: Biological Sciences.

An analysis of transient Markov decision processes

E. J. Collins, Huw James, 2006, Journal of Applied Probability.

The hawk-dove game as an average cost problem

E. J. Collins, J. McNamara, S. Merad, 1991 .

Convergent multiple-timescales reinforcement learning algorithms in normal form games

E. J. Collins, D. Leslie, 2003 .

The hidden cost of information in collective foraging

E. J. Collins, A. Houston, A. Dornhaus, 2005, Proceedings of the Royal Society B: Biological Sciences.

Generalised weakened fictitious play

David S. Leslie, Edmund J. Collins, E. J. Collins, 2006, Games Econ. Behav..

Finite-horizon variance penalised Markov decision processes

E. J. Collins, 1997 .

Finite-horizon dynamic optimisation when the terminal reward is a concave functional of the distribution of the final state

E. J. Collins, J. McNamara, 1998, Advances in Applied Probability.

Population-level reinforcement learning resulting in smooth best response dynamics

E. J. Collins, D. Leslie, 2002 .

The Bernoulli Feedback Queue with Balking: stochastic order results and equilibrium joining rules

Anthony C. Brooms, E. J. Collins, 2005 .

A general technique for computing evolutionarily stable strategies based on errors in decision-making.

E. J. Collins, A. Houston, J. McNamara, 1997, Journal of theoretical biology.

Paying for information: partial loads in central place foragers

N. R. Franks, E. J. Collins, A. Houston, 2006, Behavioral Ecology and Sociobiology.

Learning rules for optimal selection in a varying environment: mate choice revisited

David M. Ramsey, John M. McNamara, E. J. Collins, 2006 .

The job-search problem with competition: an evolutionarily stable dynamic strategy

E. J. Collins, J. McNamara, J. M. Mcnamara, 1993, Advances in Applied Probability.

The ideal free distribution: an analysis of the perceptual limit model

Alasdair I. Houston, E. J. Collins, A. Houston, 2002 .

THE JOB SEARCH PROBLEM AS AN EMPLOYER-CANDIDATE GAME

E. J. Collins, J. M. Mcnamara, 1990 .

Learn quickly, adapt slowly | convergent learning algorithms for normal form games

E. J. Collins, D. Leslie, 2003 .

Stochastic order results and equilibrium joining rules for the Bernoulli Feedback Queue

A. C. Brooms, E. J. Collins, 2013 .

The job search problem as an employer–candidate game

E. J. Collins, J. McNamara, 1990, Journal of Applied Probability.

Posterior Weighted Reinforcement Learning with State Uncertainty

David S. Leslie, Rafal Bogacz, Edmund J. Collins, 2010, Neural Computation.

Individual Q-Learning in Normal Form Games

David S. Leslie, Edmund J. Collins, E. J. Collins, 2005, SIAM J. Control. Optim..

Simple learning rules to cope with changing environments

Roderich Groß, Nigel R Franks, Alasdair I Houston, 2008, Journal of The Royal Society Interface.

Optimality Models in Behavioral Biology

Edmund J. Collins, John McNamara, E. J. Collins, 2001, SIAM Rev..

The Hawk–Dove game as an average-cost problem

E. J. Collins, J. McNamara, S. Merad, 1991, Advances in Applied Probability.

Should females prefer to mate with low-quality males?

E. J. Collins, A. Houston, Codina Cotar, 2008, Journal of theoretical biology.

Models and algorithms for skip-free Markov decision processes on trees

Edmund J. Collins, E. J. Collins, 2013, J. Oper. Res. Soc..

Posterior Weighted Reinforcement Learning with State Uncertainty

E. J. Collins, D. Leslie, R. Bogacz, 2010, Neural Computation.