Opening the black box of trust: reasoning about trust models in a BDI agent

2012 ◽  
Vol 23 (1) ◽  
pp. 25-58 ◽  
Author(s):  
A. Koster ◽  
M. Schorlemmer ◽  
J. Sabater-Mir
Author(s):  
Michael Dann ◽  
Yuan Yao ◽  
Brian Logan ◽  
John Thangarajah

We propose a new approach to intention progression in multi-agent settings where other agents are effectively black boxes. That is, while their goals are known, the precise programs used to achieve these goals are not known. In our approach, agents use an abstraction of their own program called a partially-ordered goal-plan tree (pGPT) to schedule their intentions and predict the actions of other agents. We show how a pGPT can be derived from the program of a BDI agent, and present an approach based on Monte Carlo Tree Search (MCTS) for scheduling an agent's intentions using pGPTs. We evaluate our pGPT-based approach in cooperative, selfish and adversarial multi-agent settings, and show that it out-performs MCTS-based scheduling where agents assume that other agents have the same program as themselves.


2005 ◽  
Vol 38 (7) ◽  
pp. 49
Author(s):  
DEEANNA FRANKLIN
Keyword(s):  

2005 ◽  
Vol 38 (9) ◽  
pp. 31
Author(s):  
BETSY BATES
Keyword(s):  

2007 ◽  
Vol 40 (23) ◽  
pp. 7
Author(s):  
ELIZABETH MECHCATIE
Keyword(s):  

2008 ◽  
Vol 41 (8) ◽  
pp. 4
Author(s):  
BROOKE MCMANUS
Keyword(s):  

1989 ◽  
Vol 34 (12) ◽  
pp. 1078-1080
Author(s):  
Deborah A. Phillips
Keyword(s):  

1991 ◽  
Vol 36 (6) ◽  
pp. 477-478
Author(s):  
T. K. Das
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document