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doi:10.1093/comjnl/bxh000 Agent Support for Policy-driven Collaborative Mission Planning
, 2008
"... In this paper, we describe, how agents can support collaborative planning within international coalitions, formed in an ad-hoc fashion as a response to military and humanitarian crises. As these coalitions are formed rapidly and without much lead time or co-training, human planners may be required t ..."
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Cited by 20 (13 self)
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In this paper, we describe, how agents can support collaborative planning within international coalitions, formed in an ad-hoc fashion as a response to military and humanitarian crises. As these coalitions are formed rapidly and without much lead time or co-training, human planners may be required to observe a plethora of policies that direct their planning effort. In a series of experiments, we show how agents can support human planners and ease their cognitive burden by giving advice on the correct use of policies and catch possible violations.
Arguments over Co-operative Plans
"... Abstract. Autonomous planning agents that share a common goal should be able to propose, justify and share information about plans. To reach an agreement on the best plan, strategies for persuasion and negotiation can be used by agents in order to share their beliefs about the world and resolve conf ..."
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Cited by 4 (3 self)
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Abstract. Autonomous planning agents that share a common goal should be able to propose, justify and share information about plans. To reach an agreement on the best plan, strategies for persuasion and negotiation can be used by agents in order to share their beliefs about the world and resolve conflicts between the agents. We present an argumentation scheme and associated critical questions to create and justify plan proposals where plans are combinations of actions requiring several agents for their execution. An analysis of different ways in which actions can combine is presented and then associated with the argumentation scheme and the critical questions. We believe these elements are necessary to enable agents to engage in rational debate over co-operative plan proposals. Key words: plan proposal, argumentation schemes, critical questions, co-operation. 1
On representing planning domains under uncertainty
"... Abstract—Planning is an important activity in military coali-tions and the support of an automated planning tool could help military planners by reducing the cognitive burden of their work. Current AI planning paradigms use two different types of formalism to represent the planning problem. Each of ..."
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Cited by 2 (0 self)
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Abstract—Planning is an important activity in military coali-tions and the support of an automated planning tool could help military planners by reducing the cognitive burden of their work. Current AI planning paradigms use two different types of formalism to represent the planning problem. Each of these formalisms entails different inference algorithms and representation of results. On the one hand plans in non-stochastic domains are rep-resented using declarative logic-based formalisms, an example of which is Hierarchical Task Networks (HTNs). In HTNs, domains are represented in terms of task decompositions of increased detail in relation to the actions that must be carried out. In general, declarative formalisms are easier for humans to understand. On the other hand, stochastic planning is often rep-resented in terms of large probability functions that exhaustively specify the likelihood of relevant world changes when actions are executed, as exemplified by Markov Decision Processes (MDPs). Stochastic domain specifications can easily become challenging to a human designer as the problem size increases, worse still, solver algorithms degrade quickly with increased domain size. In order to facilitate domain modeling for planning under uncertainty, we propose a method of deriving stochastic domain specifications in the MDP formalism from a description using the HTN formalism. This method can reduce the resulting MDP state-space through an intermediate representation using Binary Decision Diagrams (BDDs). The benefits of the approach are twofold: (a) the reduction of the state space, and consequent re-duction of computational burden is beneficial since it enables the representation and solving of realistic planning problems, and (b) starting from a declarative representation makes planning more comprehensible to humans, while extending the representation to stochastic domains. I.
Automated Aiding Strategies for Decentralized Planning with Interdependent Policies (Extended Abstract)
"... We discuss how agents can support collaborative planning activities within coalitions, where coalition partners plan and act according to given policies. In a set of experiments with human test subjects, we investigate how agents can aid such a collaborative planning effort and how effective they ar ..."
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Cited by 1 (1 self)
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We discuss how agents can support collaborative planning activities within coalitions, where coalition partners plan and act according to given policies. In a set of experiments with human test subjects, we investigate how agents can aid such a collaborative planning effort and how effective they are in the chosen support modes. 1.
Advance Access publication on June 24, 2009 doi:10.1093/comjnl/bxp061 Agent Support for Policy-Driven Collaborative Mission Planning
, 2008
"... In this paper, we describe how agents can support collaborative planning within international coalitions, formed in an ad hoc fashion as a response to military and humanitarian crises. As these coalitions are formed rapidly and without much lead time or co-training, human planners may be required to ..."
Abstract
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In this paper, we describe how agents can support collaborative planning within international coalitions, formed in an ad hoc fashion as a response to military and humanitarian crises. As these coalitions are formed rapidly and without much lead time or co-training, human planners may be required to observe a plethora of policies that direct their planning effort. In a series of experiments, we show how agents can support human planners, ease their cognitive burden by giving advice on the correct use of policies and catch possible violations. The experiments show that agents can effectively prevent policy violations with no significant extra cost.
Policy-driven Planning in Coalitions- a Case Study
"... Abstract. A collaborative planning effort between partners that form coalitions may be complicated by policies that regulate what actions they may deploy in their plans and, in particular, what information they are allowed to exchange during the planning process. We are interested in situations wher ..."
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Abstract. A collaborative planning effort between partners that form coalitions may be complicated by policies that regulate what actions they may deploy in their plans and, in particular, what information they are allowed to exchange during the planning process. We are interested in situations where coalitions have to be formed ad-hoc without much co-training. For this, we investigate how agents can support human plan-ners in producing good plans while observing the normative standards that regulate their planning and communication behavior. Based on an implementation of such norm-processing agents, we conducted a set of experiments, where human test subjects were conducting collaborative planning tasks under the guidance of these agents. A summary of exper-imental results is provided in the paper. 1
unknown title
"... model for integrating dialogue and the execution of joint plans ..."
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