45 search results - page 2 / 9 » Learning Human-Like Opponent Behavior for Interactive Comput... |
109
Voted
AAMAS
2005
Springer
15 years 1 months ago
2005
Springer
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
116
Voted
ATAL
2010
Springer
15 years 2 months ago
2010
Springer
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
115
Voted
AAMAS
2002
Springer
15 years 1 months ago
2002
Springer
Abstract. Open systems are becoming increasingly important in a variety of distributed, networked computer applications. Their characteristics, such as agent diversity, heterogenei...
113
Voted
JDCTA
2010
14 years 8 months ago
2010
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...
83
Voted
AAAI
1996
15 years 2 months ago
1996
Agents that operate in a multi-agent system need an efficient strategy to handle their encounters with other agents involved. Searching for an optimal interactive strategy is a ha...