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NIPS
1993
15 years 6 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
AAMAS
2007
Springer
15 years 5 months ago
A framework for meta-level control in multi-agent systems
Sophisticated agents operating in open environments must make decisions that efficiently trade off the use of their limited resources between dynamic deliberative actions and dom...
Anita Raja, Victor R. Lesser
123
Voted
IANDC
2008
84views more  IANDC 2008»
15 years 5 months ago
A theory of system behaviour in the presence of node and link failure
We develop a behavioural theory of distributed programs in the presence of failures such as nodes crashing and links breaking. The framework we use is that of D, a language in whi...
Adrian Francalanza, Matthew Hennessy
AI
1999
Springer
15 years 4 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
NLE
2007
148views more  NLE 2007»
15 years 4 months ago
Abbreviated text input using language modeling
We address the problem of improving the efficiency of natural language text input under degraded conditions (for instance, on mobile computing devices or by disabled users), by ta...
Stuart M. Shieber, Rani Nelken