TY - GEN
T1 - Increasing Threshold Search for Best-Valued Agents
AU - Sarne, D.
AU - Shamoun, Simon
AU - Rata, Eli
N1 - Place of conference:USA
PY - 2010
Y1 - 2010
N2 - This paper investigates search techniques for multi-agent settings
in which the most suitable agent, according to given
criteria, needs to be found. In particular, it considers the case
where the searching agent incurs a cost for learning the value
of an agent and the goal is to minimize the expected overall
cost of search by iteratively increasing the extent of search.
This kind of search is applicable to various domains, including
auctions, first responders, and sensor networks. Using an
innovative transformation of the extents-based sequence to a
probability-based one, the optimal sequence is proved to consist
of either a single search iteration or an infinite sequence
of increasing search extents. This leads to a simplified characterization
of the the optimal search sequence from which it
can be derived. This method is also highly useful for legacy
economic-search applications, where all agents are considered
suitable candidates and the goal is to optimize the search
process as a whole. The effectiveness of the method for both
best-valued search and economic search is demonstrated numerically
using a synthetic environment.
AB - This paper investigates search techniques for multi-agent settings
in which the most suitable agent, according to given
criteria, needs to be found. In particular, it considers the case
where the searching agent incurs a cost for learning the value
of an agent and the goal is to minimize the expected overall
cost of search by iteratively increasing the extent of search.
This kind of search is applicable to various domains, including
auctions, first responders, and sensor networks. Using an
innovative transformation of the extents-based sequence to a
probability-based one, the optimal sequence is proved to consist
of either a single search iteration or an infinite sequence
of increasing search extents. This leads to a simplified characterization
of the the optimal search sequence from which it
can be derived. This method is also highly useful for legacy
economic-search applications, where all agents are considered
suitable candidates and the goal is to optimize the search
process as a whole. The effectiveness of the method for both
best-valued search and economic search is demonstrated numerically
using a synthetic environment.
UR - https://scholar.google.co.il/scholar?q=Increasing+Threshold+Search+for+Best-Valued+Agents+&btnG=&hl=en&as_sdt=0%2C5
M3 - Conference contribution
BT - AAAI
ER -