1 Fuzzy Quantification of Trust Punam Bedi Department of Computer Science, University of Delhi, Delhi – 110007, India. Email: punam_bedi@hotmail.com Harmeet Kaur Department of Computer Science, Hans Raj College, University of Delhi, Delhi- 110007, India. Email: harmeet_negi@rediffmail.com Abstract The presence of trust in human society is unquestionable and as agents are designed to behave like humans, trust should play an important role as a characteristic of an agent. Trust in humans is subjective and non- dichotomous. The linguistic terms are generally used by humans to discuss trust. However, quantification of trust is required to make the concept usable for the agents. This paper proposes a trust model that uses the fuzzy set theory to compute trust from the linguistic terms. The non-dichotomous nature of trust is taken care of by the fuzzy sets. The capability of the trustee, the past experience in dealing with the trustee, the recommendations of experts and the external factors are used in the proposed trust model to compute trust. Keywords : Trust, Agent, Fuzzy, Linguistic terms, Referral trust 1. Introduction The Oxford dictionary defines trust as “n. firm belief that a person or thing maybe relied on; confident expectation; responsibility”. In literature, trust is defined as a subjective probability by which an individual expects that the other entity (the entity can be a human, a software agent, an organization or a machine) will perform a given action on which its welfare depends, i.e., some predictability is expected in the behavior of the other entity. Trust is subjective in human beings, but for agents to be able to make use of trust, some quantification is required. The researchers are using various models to evaluate trust. An example on file downloading is given and the parameters, like downloading speed, etc., that are relevant to a trustworthy interaction in file downloading are considered in Bayesian Network - Based Trust Model [16]. A specific application of computing trust of a doctor using Fuzzy Cognitive Maps with the fuzzy parameters is given in Cooperating through Belief - based Trust Computation [3]. In this paper, ability, availability and unharmfulness are considered as internal factors; and opportunity and danger are considered as the external factors. An algorithmic form for computation of trust, using past experiences and recommendations from other agents is given in Trust Based Knowledge Outsourcing for Semantic Web Agents [8]. External factors are considered in [3] and [4] but not much emphasis is given to them, which can alter the behavior of even highly trustworthy entities. When we interact with other human beings to inquire about the trustworthiness of an entity, we don’t expect the answer to be a numerical value rather we expect a linguistic term [1], say HIGHLY TRUSTWORHY, etc. So when we are designing intelligent agents that behave like humans then preferably they should interact with each other using the same terminology as humans to make them more believable. In literature, some work on trust based on fuzzy concept [3, 4] is done, but these papers also do not consider fuzziness in terms of linguistic variables. In our paper, a generic trust model is proposed in which various external factors are taken into consideration in addition to capability of the trustee, past dealings with the trustee and the recommendations from other entities about the trustee. This paper is organized as follows. In Section 2, we discuss the importance of trust in humans and agents. The Sections 3, discusses how trust depends upon capability, the Section 4 gives the influence of past experience in dealing with the trustee agent and the Section 5, discusses the impact of recommendations about the trustee agent from other agents. The Section 6 discusses the proposed the trust model based on fuzzy set theory. The influence of external factors on computation of trust is also discussed in this section.