Distributed Belief Revision and Environmental Decision Support

Conservation Biology, 2014

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group.

Environment and Planning B: Planning and Design, 1992

One way to tailor analysis to the special information needs of multiparty decisionmaking processes is discussed. A scenario-based multiattribute trade-off analysis framework is described that parallels the stages in negotiated decisionmaking, focusing on the key task of evaluating trade-offs among choices en route to a consensus decision. Sorting techniques with carefully managed normative content are employed to reveal overlapping preferences regarding choices among alternatives in spite of widely divergent views about fundamental issues. The same techniques are also shown to be useful for closing gaps in negotiating positions. These concepts are illustrated with data from a recent energy and environmental planning application.

Scientific Reports

is power"-holds the popular proverb, because knowledge and information is indeed one of the cornerstones of effective decision making, a requisite all living beings face continually. In fact, effective decision making is a matter of life and death, for individuals and groups alike. Furthermore, in case of group decisions, consensus is also often desirable. This latter one has been studied extensively by means of formal (mathematical) tools (in the field of opinion dynamics), while the first requirement, the process of yielding accurate information has been largely neglected, at least so far. In the present paper we study the optimal structure of groups which are embedded into an external, observable environment for (i) reaching consensus (ii) having well-informed members, and (iii) for those cases when both aspects are equally important. The groups are characterised by their communication networks and individual properties. We find that the group structures fundamentally differ from each other since having well-informed members requires highly specialised individuals embedded into a structured communication network, while consensus is promoted by non-hierarchical networks in which individuals participate equally. We also find that-contrary to intuition-high access to information calls forth hierarchy, and that suggestibility promotes accuracy, not consensus. According to Nobel-laureate Daniel Kahneman, "Whatever else it produces, an organization is a factory that manufactures judgments and decisions" 1. These decisions are of many kinds: they can relate to new investments, fundraising, change of profile, the hire of new employees, adaptation of new technologies, expansions to new areas-just to mention a few. What is common in these cases is that they are usually made by a few-top a most a few dozen 2-decision makers, all of whom have only partial access to the information necessary to make well-founded decisions: for example, considering a company, one of the decision-makers might have detailed information regarding the law environment in the country they are considering new investment in; an other one might be familiar with the local education system and the quality of expertise; a third member might be informed regarding the conditions of the local market, etc. In other words, different individuals see different aspects, "facets" of the same problem, and only in the most simple cases do all decision-makers oversee all the aspects, the complete "environment"-an observable "external reality" which includes important information regarding the problem or situation to be decided about. From a more general point of view, not only organizations, but all communities-animal and human alikeare "decision making factories", since all of them face a constant pressure for making collective decisions 3-6 (By "community" we mean a group with more or less stable membership performing common actions 7). Moreover, the quality of these decisions are of fundamental importance, since often the very existence of the group depends on them: if an animal gang makes a mistake regarding the safety or position of a night-lair, it might easily be attacked by predators. If a flock of birds navigates incorrectly towards its winter location, it might easily lose its way and find itself in cold or nutrition-poor locations. If the decision-making board of a company takes a bad decision regarding a new investment, it might easily go bankrupt. In these (and many other real-life) cases the quality of the decisions fundamentally depend on the accuracy and completeness of information regarding the environment 8,9. In short, complete and accurate information is a fundamental requirement for making good decisions 10,11. Furthermore, in case of groups, consensus plays a central role as well, since it ensures cohesive, close-knit communities by warranting the feeling for the members that they create their future together (As a

1998

In a real world multiagent system, where the agents are faced with partial, incomplete and intrinsically dynamic knowledge, conflicts are inevitable. Frequently, different agents have goals or beliefs that cannot hold simultaneously. Conflict resolution methodologies have to be adopted to to overcome such undesirable occurrences. In this paper we investigate the application of distributed belief revision techniques as the support

The Environmentalist, 2006

The paper presents a method of participatory decision-making involving the authorities at local level, experts and the public. It studies how to solve the problems caused by the heterogeneity of the parties taking part in the decision-making process. The method builds on mutual learning and consideration among the participants following a systematic approach led by a moderator. The method was tested at a workshop simulating a real-life situation. The test case studied at the workshop was the problem of identifying the best site for a low and intermediate level radioactive waste repository among three alternatives. The learning phase was the Krško Nuclear Power Plant cooling problem. The results show that the participants were able to reach agreement on the prioritisation of the alternatives and to end up with suprisingly complex and fully reasonable decision models. We believe that this was achieved particularly due to the well defined procedure that guided the decision-making process, and the ability of all participants to see the influence of their views on the decision model.

NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society, 2008

Reaching consensus is a crucial objective in multicriteria and multiagent decision making. To this aim some perspectives are here studied, such as a geometric representation and a game theoretical modelling. This is a start point for a definition of a consensus activating procedure.

The ability to respond sensibly to changing and conflicting beliefs is an integral part of intelligent agency. To this end, we outline the design and implementation of a Distributed Assumption-based Truth Maintenance System (DATMS) appropriate for controlling cooperative problem solving in a dynamic real world multi-agent community. Our DATMS works on the principle of local coherence which means that different agents can have different perspectives on the same fact provided that these stances are appropriately ...

Ecology and Society 12 (1): 5., 2007

"We survey and evaluate selected participatory tools that have been proven effective in natural resources management and research during our extensive experience with forest communities. We first establish a framework for our analysis by identifying a set of criteria for evaluating each tool. Next we provide a brief description of each tool, followed by an evaluation and comparison of the strengths and weaknesses of all the tools examined and how well they can be adapted to diverse contexts. We also provide suggestions for avoiding common pitfalls. Our findings suggest that most tools are flexible enough to be adapted to a range of applications, and that results are more robust when tools are used in concert. Practitioners should not be disturbed when results are contradictory or unexpected; initial surprises can lead to unexpected discoveries. Given the complexity of natural resources and their management, picking the right tool does not guarantee that the data desired will be produced, but selecting the wrong tool does make success less likely. The tools assessed are Bayesian belief networks and system dynamic modeling tools, discourse-based valuation, the 4Rs framework, participatory mapping, scoring or the Pebble Distribution Method, future scenarios, spidergrams, Venn diagrams, and Who Counts Matrices."

Studies in Computational Intelligence, 2008

Procedia Technology, 2013