A Replanning Algorithm for Decision Theoretic Hierarchical Planning: Principles and Empirical Evaluation

Boella, Guido; Damiano, Rossana

doi:10.1080/08839510802379584

Cited by 3 publications

(4 citation statements)

References 66 publications

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“…We give some illustrative examples of this behaviour based on the above scenario in Sect. 3. This point exhibits of one of the technical challenges that we address in this article: determining the precise sequence of actions once a parent goal or plan is aborted or suspended.…”

Section: Discussionmentioning

confidence: 97%

“…Rather, cleaning up may involve compensation via forward recovery actions [3]. We discuss this in more detail in Sect.…”

Section: Discussionmentioning

confidence: 99%

“…The question of what to do when resuming a suspended plan, should circumstances have changed, has been considered in the AI planning literature (e.g., [3]). On the one hand, an agent may appraise world state to see if the plan is still applicable.…”

Section: Related Workmentioning

confidence: 99%

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Aborting, suspending, and resuming goals and plans in BDI agents

Harland

Morley

Thangarajah

et al. 2015

Auton Agent Multi-Agent Syst

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Intelligent agents designed to work in complex, dynamic environments such as ecommerce must respond robustly and flexibly to environmental and circumstantial changes, including the actions of other agents. An agent must have the capability to deliberate about appropriate courses of action, which may include reprioritising tasks-whether goals or associated plans-aborting or suspending tasks, or scheduling tasks in a particular order. In this article we study mechanisms to enable principled suspend, resuming, and aborting of goals and plans within a Belief-Desire-Intention (BDI) agent architecture. We give a formal and combined operational semantics for these actions in an abstract agent language (CAN), thus providing a general mechanism that can be incorporated into several BDI-based agent platforms. The abilities enabled by our semantics provides an agent designer greater flexibility to direct agent operation, offering a generic means to manage the status of goals. We demonstrate the reasoning abilities enabled on a document workflow scenario.

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Section: Discussionmentioning

confidence: 97%

“…Rather, cleaning up may involve compensation via forward recovery actions [3]. We discuss this in more detail in Sect.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Aborting, suspending, and resuming goals and plans in BDI agents

Harland

Morley

Thangarajah

et al. 2015

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

show abstract

“…Finally, the system does not support interactivity, since the resulting plan devised by the decision making component is directly executed in the 3D virtual world with no reconsideration in case of failures. Since the paradigm of HTN planning can easily be adapted to deal with replanning [34,35], we intend to expand the system to interactive animated agents.…”

Section: Discussionmentioning

confidence: 99%

Virtual agents for the production of linear animations

Damiano

Lombardo

Nunnari

2013

Entertainment Computing

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In the last decade, a number of techniques from the new media practices have contributed to innovate the traditional production of entertainment, through the modularization and the automation of a number of phases. This paper proposes a novel approach to the automatic generation of character animations that draws inspiration from the techniques for the construction of the virtual agents. The pipeline for the production of animated scenes is based on the mapping between the authorial description of characters' behavior and the actual animation data. The application context is the production of linear (non interactive) animations. Given the specification of a set of high level goals, the implemented system generates the animation through the generation of a sequence of actions, the translation of actions into animation commands, the display of an animated scene through a 3D graphic engine. The pipeline and the system are validated onto the production of a short animated movie, with the participation of a commercial company.

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HIPR: An Architecture for Iterative Plan Repair in Hierarchical Multi-agent Systems

Mohalik¹

2018

JCP

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In large scale multi-agent systems, both planning for system goals and replanning during plan execution to handle failures are compute-intensive. Since replanning requires faster response time because it happens during plan execution, a lot of focus in the AI planning literature has been on incremental methods, such as plan repair, plan modification etc., which avoid re-synthesizing a complete plan. In this paper, we propose HIPR-an architecture and supporting algorithms for fast replanning in multi-agent systems with two fairly general characteristics: (1) where the agents are organized hierarchically based on attributes like location/administration and (2) where most failures are localized i.e. only a few agents are affected by the failure while most of the agents at large remain unaffected. HIPR exploits these characteristics to identify the smallest group of agents that are affected by the failure and to synthesize new plan fragments for only these agents. The localization to smaller number of agents generates smaller replanning problems and hence more efficient solutions. We illustrate application of HIPR on a small, yet realistic route planning use case.

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A Replanning Algorithm for Decision Theoretic Hierarchical Planning: Principles and Empirical Evaluation

Cited by 3 publications

References 66 publications

Aborting, suspending, and resuming goals and plans in BDI agents

Aborting, suspending, and resuming goals and plans in BDI agents

Virtual agents for the production of linear animations

HIPR: An Architecture for Iterative Plan Repair in Hierarchical Multi-agent Systems

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