Agent long-term coalition credit

Agent trust researches become more and more important because they will ensure good interactions among the software agents in large-scale open systems. Moreover, individual agents often interact with long-term coalitions such as some E-commerce web sites. So the agents should choose a coalition based on utility and trust. Unfortunately, few studies have been done on agent coalition credit and there is a need to do it in detail. To this end, a long-term coalition credit model (LCCM) is presented. Furthermore, the relationship between coalition credit and coalition payoff is also attended. LCCM consists of internal trust based on agent direct interactions and external reputation based on agent direct observation. Generalization of LCCM can be demonstrated through experiments applied in both cooperative and competitive domain environment. Experimental results show that LCCM is capable of coalition credit computation efficiently and can properly reflect various factors effect on coalition credit. Another important advantage that is a useful and basic property of credit is that LCCM can effectively filter inaccurate or lying information among interactions.