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AAAI
2008
13 years 7 months ago
Perpetual Learning for Non-Cooperative Multiple Agents
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
Luke Dickens
ATAL
2009
Springer
13 years 11 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
NECO
2007
150views more  NECO 2007»
13 years 4 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
ACSAC
2010
IEEE
12 years 8 months ago
A quantitative analysis of the insecurity of embedded network devices: results of a wide-area scan
We present a quantitative lower bound on the number of vulnerable embedded device on a global scale. Over the past year, we have systematically scanned large portions of the inter...
Ang Cui, Salvatore J. Stolfo