Probabilistic Search for Tracking Targets (ePub)

Presents a probabilistic and information-theoretic framework
for a search for static or moving targets in discrete time and
space.

Probabilistic Search for Tracking Targets uses an
information-theoretic scheme to present a unified approach for
known search methods to allow the development of new algorithms of
search. The book addresses search methods under different
constraints and assumptions, such as search uncertainty under
incomplete information, probabilistic search scheme, observation
errors, group testing, search games, distribution of search
efforts, single and multiple targets and search agents, as well as
online or offline search schemes. The proposed approach is
associated with path planning techniques, optimal search
algorithms, Markov decision models, decision trees, stochastic
local search, artificial intelligence and heuristic
information-seeking methods. Furthermore, this book presents novel
methods of search for static and moving targets along with
practical algorithms of partitioning and search and screening.

Probabilistic Search for Tracking Targets includes
complete material for undergraduate and graduate courses in modern
applications of probabilistic search, decision-making and group
testing, and provides several directions for further research in
the search theory.

The authors:

* Provide a generalized information-theoretic approach to the
problem of real-time search for both static and moving targets over
a discrete space.

* Present a theoretical framework, which covers known
information-theoretic algorithms of search, and forms a basis for
development and analysis of different algorithms of search over
probabilistic space.

* Use numerous examples of group testing, search and path
planning algorithms to illustrate direct implementation in the form
of running routines.

* Consider a relation of the suggested approach with known search
theories and methods such as search and screening theory, search
games, Markov decision process models of search, data mining
methods, coding theory and decision trees.

* Discuss relevant search applications, such as quality-control
search for nonconforming units in a batch or a military search for
a hidden target.

* Provide an accompanying website featuring the algorithms
discussed throughout the book, along with practical implementations
procedures.