3084 search results - page 9 / 617 » Learning to Take Actions |
DAGSTUHL
2007
13 years 8 months ago
2007
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
ECML
2005
Springer
14 years 27 days ago
2005
Springer
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
CHI
2004
ACM
14 years 7 months ago
2004
ACM
People frequently write messages to themselves. These informal, hurried personal jottings serve as temporary storage for notable information as well as reminders for future action...
NIPS
2007
13 years 8 months ago
2007
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...