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COLT
1994
Springer
15 years 10 months ago
Efficient Reinforcement Learning
Realistic domains for learning possess regularities that make it possible to generalize experience across related states. This paper explores an environment-modeling framework tha...
Claude-Nicolas Fiechter
EUROMICRO
2009
IEEE
15 years 9 months ago
Sprint Planning with a Digital Aid Tool: Lessons Learnt
- Managing the product’s backlog is a major task in agile projects. This case study reports on one organization’s experiences from the transition to a backlog management tool a...
Erlend Agoy Engum, Zornitza Racheva, Maya Daneva
AAAI
2008
15 years 8 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
NIPS
2001
15 years 7 months ago
Switch Packet Arbitration via Queue-Learning
In packet switches, packets queue at switch inputs and contend for outputs. The contention arbitration policy directly affects switch performance. The best policy depends on the c...
Timothy X. Brown
CDC
2008
IEEE
117views Control Systems» more  CDC 2008»
15 years 6 months ago
Clustering in a network of mutually attracting agents
We introduce a model of mutually attracting agents in an arbitrary network, for which the long term behavior results in the emergence of several clusters. The cluster structure is ...
Filip De Smet, Dirk Aeyels