Programming Cognitive Agents in Defeasible Logic

Defeasible Logic is extended to programming languages for cognitive agents with preferences and actions for planning. We define rule-based agent theories that contain preferences and actions, together with inference procedures. We discuss patterns of agent types in this setting. Finally, we illustrate the language by an example of an agent reasoning about web-services

Preferences of Agents in Defeasible Logic

We are interested in programming languages for cognitive agents with preferences. We define rule-based agent theories and inference procedures in defeasible logic, and in this setting we discuss patterns of agent behavior called agent types

Experimental and numerical investigation of contact parameters in a dovetail type of blade root joints

This paper focuses on the contact characteristics of the blade root joints subjected to the dry friction damping under periodic excitation. The numerical method and experimental procedure are combined to trace the contact behavior in the nonlinear vibration conditions. In experimental procedure, a novel excitation method alongside the accurate measurements is used to determine the frequencies of the blade under different axial loads. In numerical simulations, local behavior of contact areas is investigated using the reduction method as a reliable and fast solver. Subsequently, by using both experimental measurements and numerical outcomes in a developed code, the global stiffness matrix is calculated. This leads to find the normal and tangential stiffness in the contact areas of a dovetail blade root joints. The results indicate that the proposed method can provide an accurate quantitative assessment for investigation the dynamic response of the joints with focusing the contact areas

Normative Multi-Agent Programs and Their Logics

Multi-agent systems are viewed as consisting of individual agents whose behaviors are regulated by an organization artefact. This paper presents a simplified version of a programming language that is designed to implement norm-based artefacts. Such artefacts are specified in terms of norms being enforced by monitoring, regimenting and sanctioning mechanisms. The syntax and operational semantics of the programming language are introduced and discussed. A logic is presented that can be used to specify and verify properties of programs developed in this language

Semantic Mutation Testing for Multi-Agent Systems

This paper introduces semantic mutation testing (SMT) into multiagent systems. SMT is a test assessment technique that makes changes to the interpretation of a program and then examines whether a given test set has the ability to detect each change to the original interpretation. These changes represent possible misunderstandings of how the program is interpreted. SMT is also a technique for assessing the robustness of a program to semantic changes. This paper applies SMT to three rule-based agent programming languages, namely Jason, GOAL and 2APL, provides several contexts in which SMT for these languages is useful, and proposes three sets of semantic mutation operators (i.e., rules to make semantic changes) for these languages respectively, and a set of semantic mutation operator classes for rule-based agent languages. This paper then shows, through preliminary evaluation of our semantic mutation operators for Jason, that SMT has some potential to assess tests and program robustness

Strategic Executions of Choreographed Timed Normative Multi-Agent Systems

This paper proposes a combined mechanism for coordinating agents in timed normative multi-agent systems. Timing constraints in a multi-agent system make it possible to force action execution to happen before certain time invariants are violated. In such multiagent systems we achieve coordination at two orthogonal levels with respect to states and actions. On the one hand, the behaviour of individual agents is regulated by means of social and organisational inspired concepts like norms and sanctions. On the other hand, the behaviour of sets of agents is restricted according to action-based coordination mechanisms called choreographies. In both cases, the resulting behaviour is constrained by time

Reasoning about agent deliberation

We present a family of sound and complete logics for reasoning about deliberation strategies for SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementation of cognitive agents with beliefs, goals and plans. The logics are variants of PDL, and allow us to prove safety and liveness properties of SimpleAPL agent programs under different deliberation strategies. We show how to axiomatize different deliberation strategies for SimpleAPL programs, and, for each strategy we consider, prove a correspondence between the operational semantics of SimpleAPL and the models of the corresponding logic. We illustrate the utility of our approach with an example in which we show how to verify correctness properties for a simple agent program under different deliberation strategies

Inferring trust

In this paper we discuss Liau's logic of Belief, Inform and Trust (BIT), which captures the use of trust to infer beliefs from acquired information. However, the logic does not capture the derivation of trust from other notions. We therefore suggest the following two extensions. First, like Liau we observe that trust in information from an agent depends on the topic of the information. We extend BIT with a formalization of topics which are used to infer trust in a proposition from trust in another proposition, if both propositions have the same topics. Second, for many applications, communication primitiv

Probabilistic Perception Revision in AgentSpeak(L)

Agent programming is mostly a symbolic discipline and, as such, draws little benefits from probabilistic areas as machine learning and graphical models. However, the greatest objective of agent research is the achievement of autonomy in dynamical and complex environments — a goal that implies embracing uncertainty and therefore the entailed representations, algorithms and techniques. This paper proposes an innovative and conflict free two layer approach to agent programming that uses already established methods and tools from both symbolic and probabilistic artificial intelligence. Moreover, this method is illustrated by means of a widely used agent programming example, GOLDMINERS

Towards an Approach for Validating the Internet-of-Transactional-Things

© 2020, Springer Nature Switzerland AG. This paper examines the impact of transactional properties, known as pivot, retriable, and compensatable, on Internet-of-Things (IoT). Despite the ever-growing number of things in today’s cyber-physical world, a limited number of studies examine this impact while considering things’ particularities in terms of reduced size, restricted connectivity, continuous mobility, limited energy, and constrained storage. To address this gap, this paper proceeds first, with exposing things’ duties, namely sensing, actuating, and communicating. Then, it examines the appropriateness of each transactional property for each duty. During the performance of transactional things, (semi)-atomicity criterion is adopted allowing to approve when these things’ duties could be either canceled or compensated. A system that runs a set of what-if experiments is presented in the paper allowing to demonstrate the technical doability of transactional things