Policy support for autonomous swarms of drones

In recent years drones have become more widely used in military and non-military applications. Automation of these drones will become more important as their use increases. Individual drones acting autonomously will be able to achieve some tasks, but swarms of autonomous drones working together will be able to achieve much more complex tasks and be able to better adapt to changing environments. In this paper we describe an example scenario involving a swarm of drones from a military coalition and civil/humanitarian organisations that are working collaboratively to monitor areas at risk of flooding. We provide a definition of a swarm and how they can operate by exchanging messages. We define a flexible set of policies that are applicable to our scenario that can be easily extended to other scenarios or policy paradigms. These policies ensure that the swarms of drones behave as expected (e.g., for safety and security). Finally we discuss the challenges and limitations around policies for autonomous swarms and how new research, such as generative policies, can aid in solving these limitations

An Agent Architecture for Concurrent Bilateral Negotiations

Abstract. We present an architecture that makes use of symbolic decision-making to support agents participating in concurrent bilateral negotiations. The architecture is a revised version of previous work with the KGP model [23, 12], which we specialise with knowledge about the agent’s self, the negotiation opponents and the environment. Our work combines the specification of domain-independent decision-making with a new protocol for concurrent negotiation that revisits the well-known alternating offers protocol [22]. We show how the decision-making can be specialised to represent the agent’s strategies, utilities and prefer-ences using a Prolog-like meta-program. The work prepares the ground for supporting decision-making in concurrent bilateral negotiations that is more lightweight than previous work and contributes towards a fully developed model of the architecture

International Standard ISO 9001–A Soft Computing View

In order to add value to ISO 9001, a Quality Management Systems that assess, measure, documents, improves, and certify processes to increase productivity, i.e., that transforms business at any level. On the one hand, this work focuses on the development of a decision support system, which will allow companies to be able to meet the needs of customers by fulfilling requirements that reflect either the effectiveness or the non-effectiveness of an organization. On the other hand, many approaches for knowledge representation and reasoning have been proposed using Logic Programming (LP), namely in the area of Model Theory or Proof Theory. In this work it is followed the proof theoretical approach in terms of an extension to the LP language to knowledge representation and reasoning. The computational framework is centered on Artificial Neural Networks to evaluate customer’s satisfaction and the degree of confidence that one has on such a happening

PREFERRED EXTENSIONS ARE PARTIAL STABLE MODELS

We show that two recently presented proposals for the semantics of normal logic programs, namely partial stable models of Sacca and Zaniolo and preferred extensions of Phan Minh Dung coincide

KNOWLEDGE ASSIMILATION AND ABDUCTION

We argue that Abduction is useful for the problem of Knowledge Assimilation and use it to study the problems of Belief Revision and Truth Maintenance (TM) associated with the task of assimilating a series of observations Q1,...Q(n). The close connection between Abduction and TM shown in [Reiter&de Kleer87] is explored further to provide a non-monotonic extension of ATMS that incorporates a dependency-directed backtracking mechanism thus combining the capabilities of ATMS and Doyle's TMS. This TM system has a well-defined semantics inherited from the semantics for abduction which is defined through a generalization of stable models based on autoepistemic logic