Multi-agent blackboard architecture for supporting legal decision making

Our research objective is to design a system to support legal decision-making using the multi-agent blackboard architecture. Agents represent experts that may apply various knowledge processing algorithms and knowledge sources. Experts cooperate with each other using blackboard to store facts about current case. Knowledge is represented as a set of rules. Inference process is based on bottom-up control (forward chaining). The goal of our system is to find rationales for arguments supporting different decisions for a given case using precedents and statutory knowledge. Our system also uses top-down knowledge from statutes and precedents to interactively query the user for additional facts, when such facts could affect the judgment. The rationales for various judgments are presented to the user, who may choose the most appropriate one. We present two example scenarios in Polish traffic law to illustrate the features of our system. Based on these results, we argue that the blackboard architecture provides an effecive approach to model situations where a multitude of possibly conflicting factors must be taken into account in decision making. We briefly discuss two such scenarios: incorporating moral and ethical factors in decision making by autonomous systems (e.g. self-driven cars), and integrating eudaimonic (well-being) factors in modeling mobility patterns in a smart city

Incorporating human dimension in autonomous decision-making on moral and ethical issues

As autonomous systems are becoming more and more pervasive, they often have to make decisions concerning moral and ethical values. There are many approaches to incorporating moral values in autonomous decision-making that are based on some sort of logical deduction. However, we argue here, in order for decision-making to seem persuasive to humans, it needs to reflect human values and judgments. Employing some insights from our ongoing research using features of the blackboard architecture for a context-aware recommender system, and a legal decision-making system that incorporates supra-legal aspects, we aim to exploreif this architecture can also be adapted to implement a moral decision-making system that generates rationales that are persuasive to humans. Our vision is that such a system can be used as an advisory system to consider a situation from different moral pers pectives, and generate ethical pros and cons of taking a particular course of action in a given context

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Towards domain-independent conflict resolution tools

Given the current state of the legal systems, Online Dispute Resolution tools are being regarded as an alternative way to solve conflicts out of courts, namely under virtual environments. However, the use of these tools is still relatively restricted as they are still few in number and very domain-cantered. Indeed, abstract and conceptual tools whose building blocks could be adapted for particular use would foster the development of ODR systems. In this paper we present this novel line of attack, in which an agent-based architecture is used with the support of an ontology to build an abstract and formal ODR system, independent of the legal domains, but specific enough to be applied to concrete ones. Functionality reuse is maximized, making architectures simpler to implement and to expand.The work described in this paper was developed under the TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), a research project supported by FCT (Science & Technology Foundation), Portugal

Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts

The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?” Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution

A multi-agent crop production decision support system for technology transfer

The purpose of this research was to study agricultural crop production 'decision support systems' as a means of transferring agricultural technology from research labs and plots to producers, extension specialists, agriculture service agencies, and scientists, on the Western Canadian Prairies. A 'decision support system' is a computer program that analyses problems spanning several knowledge or problem areas producing results that aid the management decision-making process. The primary objective was to develop a computer application program that would fulfill the farm manager's decision support needs and be "open" to future enhancements. This interdisciplinary study has a strong agricultural presence in the application context of the resultant computerized agricultural decision support system, with agronomics being the foundation on which the system was built, and computer science being the toolbox used to build it. Farm Smart 2000 is the resultant decision support system, providing "single-window" access to three different tiers of decision support utilizing the Internet, ' expert systems' and integrated multiple heterogeneous 'reusable agents' in a cooperative problem-solving environment. An ' expert system' is a computer program that solves complicated problems, within a specific knowledge or problem area, that would otherwise require human expertise. Expert systems integrated with each other within a decision support system are called 'agents. Reusable agents' are modular computer programs (e.g. expert systems) which can be used in more than one computer application with little or no modification. Farm Smart 2000 provides support for most management aspects of crop production including variety selection, crop rotations, weed management, disease management, residue management, harvesting, soil conservation, and economics, for the crops of wheat, canola, barley, peas, and flax. Tier-3, the most sophisticated level of Farm Smart 2000, is the focus of this dissertation and utilizes multiple reusable agents, integrating them such that they cooperate together to solve complex interrelated crop production problems. A Global Control Expert achieves the required communication and coordination among the agents resulting in an "open system", enabling Farm Smart 2000 to extend its problem-solving capabilities by integrating additional agents and knowledge, without system re-engineering, thereby remaining an ongoing technology transfer vehicle

Implementation of context-aware workflows with Multi-agent Systems

Systems in Ambient Intelligence (AmI) need to manage workflows that represent users’ activities. These workflows can be quite complex, as they may involve multiple participants, both physical and computational, playing different roles. Their execution implies monitoring the development of the activities in the environment, and taking the necessary actions for them and the workflow to reach a certain end. The context-aware approach supports the development of these applications to cope with event processing and regarding information issues. Modeling the actors in these context-aware workflows, where complex decisions and interactions must be considered, can be achieved with multi-agent systems. Agents are autonomous entities with sophisticated and flexible behaviors, which are able to adapt to complex and evolving environments, and to collaborate to reach common goals. This work presents architectural patterns to integrate agents on top of an existing context-aware architecture. This allows an additional abstraction layer on top of context-aware systems, where knowledge management is performed by agents.This approach improves the flexibility of AmI systems and facilitates their design. A case study on guiding users in buildings to their meetings illustrates this approach