TY  - BOOK
AU  - Kochenderfer, Mykel J. 
AU  - Wheeler , Tim A
AU  - Wray,  Kyle H 
TI  - Algorithms for Decision Making
SN  - 9780262047012
PY  - 2022///
CY  - London
PB  - MIT Press
KW  -  Algorithms
KW  -  Probability theory
KW  -  Bayesian networks
KW  -   Multiagent systems
N1  - Includes references and index
N2  - The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented
ER  -