TY - GEN

T1 - Physical Search Problems Applying Economic Search Models

AU - Aumann, Y

AU - Hazon, N

AU - Kraus, S

AU - Sarne, D

N1 - Place of conference:USA

PY - 2008

Y1 - 2008

N2 - This paper considers the problem of an agent searching for a
resource or a tangible good in a physical environment, where
at each stage of its search it observes one source where this
good can be found. The cost of acquiring the resource or
good at a given source is uncertain (a-priori), and the agent
can observe its true value only when physically arriving at the
source. Sample applications involving this type of search include
agents in exploration and patrol missions (e.g., an agent
seeking to find the best location to deploy sensing equipment
along its path). The uniqueness of these settings is that the
expense of observing the source on each step of the process
derives from the last source the agent explored. We analyze
three variants of the problem, differing in their objective:
minimizing the total expected cost, maximizing the success
probability given an initial budget, and minimizing the
budget necessary to obtain a given success probability. For
each variant, we first introduce and analyze the problem with
a single agent, either providing a polynomial solution to the
problem or proving it is NP-Complete. We also introduce an
innovative fully polynomial time approximation scheme algorithm
for the minimum budget variant. Finally, the results
for the single agent case are generalized to multi-agent settings.

AB - This paper considers the problem of an agent searching for a
resource or a tangible good in a physical environment, where
at each stage of its search it observes one source where this
good can be found. The cost of acquiring the resource or
good at a given source is uncertain (a-priori), and the agent
can observe its true value only when physically arriving at the
source. Sample applications involving this type of search include
agents in exploration and patrol missions (e.g., an agent
seeking to find the best location to deploy sensing equipment
along its path). The uniqueness of these settings is that the
expense of observing the source on each step of the process
derives from the last source the agent explored. We analyze
three variants of the problem, differing in their objective:
minimizing the total expected cost, maximizing the success
probability given an initial budget, and minimizing the
budget necessary to obtain a given success probability. For
each variant, we first introduce and analyze the problem with
a single agent, either providing a polynomial solution to the
problem or proving it is NP-Complete. We also introduce an
innovative fully polynomial time approximation scheme algorithm
for the minimum budget variant. Finally, the results
for the single agent case are generalized to multi-agent settings.

UR - https://scholar.google.co.il/scholar?q=Physical+Search+Problems+Applying+Economic+Search+Models+&btnG=&hl=en&as_sdt=0%2C5

UR - https://scholar.google.co.il/scholar?q=Physical+search+problems+applying+economic+search+models&btnG=&hl=en&as_sdt=0%2C5

M3 - Conference contribution

BT - AAAI

ER -