Norm negotiation in multiagent systems

Normative multiagent systems provide agents with abilities to autonomously devise societies and organizations coordinating their behavior via social norms and laws. In this paper we study how agents negotiate new social norms and when they accept them. We introduce a negotiation model based on what we call the social delegation cycle, which explains the negotiation of new social norms from agent desires in three steps. First individual agents or their representatives negotiate social goals, then a social goal is negotiated in a social norm, and finally the social norm is accepted by the agents when it leads to fulfilment of the desires the cycle started with. We characterize the allowed proposals during social goal negotiation as mergers of the individual agent desires, and we characterize the allowed proposals during norm negotiation as both joint plans to achieve the social goal (obligations associated with the norm) and the associated sanctions or rewards (a control system associated with the norm). The norm is accepted when the norm is stable in the sense that agents will act according to the norm, and effective in the sense that fulfilment of the norm leads to achievement of the agents’ desires. We also compare norm negotiation with contract negotiation and negotiation of the distribution of obligation

An interaction protocol for bidirectional deliberation on direct help in agent teamwork.

This thesis proposes a new interaction protocol for direct help in agent teamwork. It addresses design questions that may arise in practical systems development, and achieves higher teamwork performance impact than previous versions of the Mutual Assistance Protocol (MAP). Direct help, such as performing an action on teammate's behalf, is deliberated by team members as need arises, rather than imposed by team organization or centralized mechanisms. The deliberation can start with a request for help, or with an offer of help the two design principles have been embodied in two distinct versions of MAP. Based on their observed complementarity, we refine and combine them into a single protocol that leverages their individual advantages. Its novel features let an agent initiate help deliberation with request or offer, and also simultaneously provide and receive help. Simulation experiments demonstrate its team performance gains while varying the environment dynamism, agent resources, and communication costs. --Leaf i.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b200687

CernoCAMAL : a probabilistic computational cognitive architecture

This thesis presents one possible way to develop a computational cognitive architecture, dubbed CernoCAMAL, that can be used to govern artificial minds probabilistically. The primary aim of the CernoCAMAL research project is to investigate how its predecessor architecture CAMAL can be extended to reason probabilistically about domain model objects through perception, and how the probability formalism can be integrated into its BDI (Belief-Desire-Intention) model to coalesce a number of mechanisms and processes. The motivation and impetus for extending CAMAL and developing CernoCAMAL is the considerable evidence that probabilistic thinking and reasoning is linked to cognitive development and plays a role in cognitive functions, such as decision making and learning. This leads us to believe that a probabilistic reasoning capability is an essential part of human intelligence. Thus, it should be a vital part of any system that attempts to emulate human intelligence computationally. The extensions and augmentations to CAMAL, which are the main contributions of the CernoCAMAL research project, are as follows: - The integration of the EBS (Extended Belief Structure) that associates a probability value with every belief statement, in order to represent the degrees of belief numerically. - The inclusion of the CPR (CernoCAMAL Probabilistic Reasoner) that reasons probabilistically over the goal- and task-oriented perceptual feedback generated by reactive sub-systems. - The compatibility of the probabilistic BDI model with the affect and motivational models and affective and motivational valences used throughout CernoCAMAL. A succession of experiments in simulation and robotic testbeds is carried out to demonstrate improvements and increased efficacy in CernoCAMAL’s overall cognitive performance. A discussion and critical appraisal of the experimental results, together with a summary, a number of potential future research directions, and some closing remarks conclude the thesis

CernoCAMAL : a probabilistic computational cognitive architecture

This thesis presents one possible way to develop a computational cognitive architecture, dubbed CernoCAMAL, that can be used to govern artificial minds probabilistically. The primary aim of the CernoCAMAL research project is to investigate how its predecessor architecture CAMAL can be extended to reason probabilistically about domain model objects through perception, and how the probability formalism can be integrated into its BDI (Belief-Desire-Intention) model to coalesce a number of mechanisms and processes.The motivation and impetus for extending CAMAL and developing CernoCAMAL is the considerable evidence that probabilistic thinking and reasoning is linked to cognitive development and plays a role in cognitive functions, such as decision making and learning. This leads us to believe that a probabilistic reasoning capability is an essential part of human intelligence. Thus, it should be a vital part of any system that attempts to emulate human intelligence computationally.The extensions and augmentations to CAMAL, which are the main contributions of the CernoCAMAL research project, are as follows:- The integration of the EBS (Extended Belief Structure) that associates a probability value with every belief statement, in order to represent the degrees of belief numerically.- The inclusion of the CPR (CernoCAMAL Probabilistic Reasoner) that reasons probabilistically over the goal- and task-oriented perceptual feedback generated by reactive sub-systems.- The compatibility of the probabilistic BDI model with the affect and motivational models and affective and motivational valences used throughout CernoCAMAL.A succession of experiments in simulation and robotic testbeds is carried out to demonstrate improvements and increased efficacy in CernoCAMAL’s overall cognitive performance. A discussion and critical appraisal of the experimental results, together with a summary, a number of potential future research directions, and some closing remarks conclude the thesis