Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fire-prone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS.

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Wildfire risk as a socioecological pathology

This work outlines a computational model of situation awareness. This model serves two purposes. First, it provides a detailed description for our everyday notion of situation awareness. Second, it offers an alternative perspective of looking into the nature and characteristics of proactive behavior in intelligent agent systems. Most of the existing definitions of proactiveness do not possess the relevant details to encourage rigorous studies of enhancing an agent's capability to anticipate and deal with foreseeable situations. This work intends to fill this gap by suggesting a working definition of proactiveness, which place additional emphasis on its underpinning cognitive process and its role in directing an agent's attention. A brief discussion of using situation awareness as meta-level control to direct a resource-bounded agent's attention is also included.

Situation awareness in intelligent agents: foundations for a theory of proactive agent behavior

Virtual characters in (serious) games are increasingly required to perform complex tasks in dynamic virtual environments. The use of BDI-agents seems a good fit to realize the intelligent behavior for virtual characters. However, although perception is part of the BDI model, it is not really geared towards real time virtual environments. In this paper we present a framework for perceptual attention for BDI-agents embodied in a virtual environment in the scope of a middleware for connecting a multi-agent system and a game engine. Attention for agents is controlled using an underlying subscription mechanism for sensing the environment. Evaluations are provided based on an implemention of the framework.

Scalable Perception for BDI-Agents Embodied in Virtual Environments

This paper discusses the need to incorporate the notion of active perception in intelligent agent systems. There are two justifications for this proposition. First, we believe perception should receive more attention and some special treatment. Perception is the most direct and effective way to update an agent's beliefs about the status of its environment. In theory, an overwhelming portion of an agent's decisions about its next course of action, or next actions, in either the reactive or deliberative model, should be heavily influenced by what is happening in the environment --- this is one of the important characteristics that differentiates agents from the traditional software design paradigm. An agent's internal activities, such as deliberation and means-end analysis, to a large extent, are also driven by what have been sensed. The second justification is that active perception plays an imperative role in situation awareness. Active perception is an important capability that directs an agent's limited attention to the relevant aspects of the environment in an proactive manner.

The Roles of Active Perception in Intelligent Agent Systems

Agent coordination and cooperation co-exist in a multiagent system, and are cognitively linked. This link is emphasized further by incorporating their atomic composition with their ability to perceive and gather information from the environment around them. As a result, a new generation of coordination/cooperation architectures is starting to emerge. From each of their definitions and current implementations, we show how the relationship between the Belief-Desire-Intention (BDI) architecture and the Observe-Orient-Decide-Act (OODA) loop can enable the use of Coordinative Cooperation within the Agent Coordination and Cooperation Cognitive Model. More importantly, we show the relationship between coordination, cooperation, BDI and OODA. This paper also discusses the current developments of the model and how the BDI and OODA architectures can affect coordination and cooperation within a Multi-Agent System (MAS). We recommend how these concepts can be designed and implemented in a MAS.

An architecture for agent coordination and cooperation

This paper introduces a notion of forward thinking agents. Recent research in situation awareness and anticipatory behavior provides useful insights and the relevant cognitive underpinnings that can be used to design adaptive software agents that capitalize on the environmental cues and their repercussions in the context of motivational autonomy. In particular, we are interested in building software agents that exhibit non-trivial anticipatory behaviors - exploiting knowledge about the current situation and the future to improve their current behavior. Some of the key issues pertaining to the realization of forward thinking, anticipatory behavior and situation awareness in agency will be briefly discussed. A conceptual extension to the generic BDI framework is also presented as part of our initial efforts in tackling some of these issues.

Raymond So

Papers

The Roles of Active Perception in Intelligent Agent Systems

Agents with initiative: A preliminary report

Agents with initiative: a preliminary report