Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Formal verification of ethical choices in autonomous systems

http://www0.cs.ucl.ac.uk/staff/a.hunter/papers/hk10.pdf

On the measure of conflicts: Shapley Inconsistency Values

http://www.cse.unsw.edu.au/~mit/Papers/AIJ07.pdf

Iterated belief revision, revised

The 1985 paper by Carlos Alchourrn (1931-1996), Peter Gardenfors, and David Makinson (AGM), "On the Logic of Theory Change: Partial Meet Contraction and Revision Functions" was the starting-point o ...

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AGM 25 Years : Twenty-Five Years of Research in Belief Change

Action formalisms like the fluent calculus have been developed to endow logic-based agents with the abilities to reason about the effects of actions, to execute high-level strategies, and to plan. In this paper we extend the fluent calculus by a method for belief change, which allows agents to revise their internal model upon making observations that contradict this model. Unlike the existing combination of the situation calculus with belief revision [16], our formalism satisfies all of the standard postulates for (iterated) belief change. Furthermore, we have extended the high-level action programming language FLUX by a computational approach to belief change which is provably equivalent to the axiomatic characterization in the fluent calculus.

Representing beliefs in the fluent calculus

https://www.cs.sfu.ca/~jim/publications/AIJ12.pdf

Parallel belief revision: Revising by sets of formulas

The AGM postulates for belief revision, augmented by the DP postulates for iterated belief revision, provide generally accepted criteria for the design of operators by which intelligent agents adapt their beliefs incrementally to new information. These postulates alone, however, are too permissive: They support operators by which all newly acquired information is canceled as soon as an agent learns a fact that contradicts some of its current beliefs. In this paper, we present a formal analysis of the deficiency of the DP postulates, and we show how to solve the problem by an additional postulate of independence. We give a representation theorem for this postulate and prove that it is compatible with AGM and DP.

/pdf/iterated-belief-revision-revised-45heyr9ry8.pdf

This paper presents both a semantic and a computational model for multi-agent belief revision. We show that these two models are equivalent but serve different purposes. The semantic model displays the intuition and construction of the belief revision operation in multi-agent environments, especially in case of just two agents. The logical properties of this model provide strong justifications for it. The computational model enables us to reassess the operation from a computational perspective. A complexity analysis reveals that belief revision between two agents is computationally no more demanding than single agent belief revision.

/pdf/mutual-belief-revision-semantics-and-computation-12pedub2uq.pdf

Yi Jin

Papers

Iterated belief revision, revised

Representing beliefs in the fluent calculus

Parallel belief revision: Revising by sets of formulas

Iterated belief revision, revised

Mutual belief revision: semantics and computation