34 search results - page 2 / 7 » Playout Policy Adaptation for Games |
TCOM
2010
13 years 3 months ago
2010
Abstract—This paper considers an uplink time division multiple access (TDMA) cognitive radio network where multiple cognitive radios (secondary users) attempt to access a spect...
AAAI
2007
13 years 7 months ago
2007
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
VALUETOOLS
2006
ACM
13 years 10 months ago
2006
ACM
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
ICML
1994
IEEE
13 years 8 months ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
ECAI
2006
Springer
13 years 8 months ago
2006
Springer
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...