TY - GEN
T1 - Colored trails: a formalism for investigating decision-making in strategic environments
AU - Gal, Y. A
AU - Grosz, B. J
AU - Kraus, S
AU - Pfeffer, A
AU - Shieber, S
N1 - Place of conference:Scotland
PY - 2005
Y1 - 2005
N2 - Colored Trails is a research testbed for analyzing
decision-making strategies of individuals or
of teams. It enables the development and testing
of strategies for automated agents that operate
in groups that include people as well as computer
agents. The testbed is based on a conceptually
simple but highly expressive game in which
players, working individually or in teams, make
decisions about how to deploy their resources to
achieve their individual or team goals. The complexity
of the setting may be increased along several
dimensions by varying the system parameters.
The game has direct analogues to real-world task
settings, making it likely that results obtained using
Colored Trails will transfer to other domains. We
describe several studies carried out using the formalism,
which investigated the effect of different
social settings on the negotiation strategies of both
people and computer agents. Using machine learning,
results from some of these studies were used to
train computer agents. These agents outperformed
other computer agents that used traditional game
theoretic reasoning to guide their behavior, showing
that CT provides a better basis for the design of
computer agents in these types of settings.
AB - Colored Trails is a research testbed for analyzing
decision-making strategies of individuals or
of teams. It enables the development and testing
of strategies for automated agents that operate
in groups that include people as well as computer
agents. The testbed is based on a conceptually
simple but highly expressive game in which
players, working individually or in teams, make
decisions about how to deploy their resources to
achieve their individual or team goals. The complexity
of the setting may be increased along several
dimensions by varying the system parameters.
The game has direct analogues to real-world task
settings, making it likely that results obtained using
Colored Trails will transfer to other domains. We
describe several studies carried out using the formalism,
which investigated the effect of different
social settings on the negotiation strategies of both
people and computer agents. Using machine learning,
results from some of these studies were used to
train computer agents. These agents outperformed
other computer agents that used traditional game
theoretic reasoning to guide their behavior, showing
that CT provides a better basis for the design of
computer agents in these types of settings.
UR - https://scholar.google.co.il/scholar?q=%09Colored+Trails%3A+A+Formalism+for+Investigating+Decision-making+in+Strategic+Environments&btnG=&hl=en&as_sdt=0%2C5
M3 - Conference contribution
BT - 2005 IJCAI workshop on reasoning, representation, and learning in computer games
ER -