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chap6.bib
@INPROCEEDINGS{Brenner:2008,
AUTHOR = {Michael Brenner},
TITLE = {Continual Collaborative Planning for Mixed-Initiative Action and
Interaction (short paper)},
BOOKTITLE = {Proc. of 7th Int. Conf. on Autonomous Agents and Multiagent Systems
(AAMAS 2008)},
YEAR = {2008},
EDITOR = {Padgham and Parkes and M\"uller and Parsons},
ADDRESS = {Estoril, Portugal},
ABSTRACT = {Multiagent environments are often highly dynamic and only partially
observable which makes deliberative action planning computationally
hard. In many such environments, however, agents can take a more
proactive approach and suspend planning for partial plan execution,
especially for active information gathering and interaction with
others. This paper presents a new algorithm for Continual Collaborative
Planning (CCP) that enables agents to deliberately interleave planning,
acting, perception and communication. Our implementation of CCP has
been evaluated with MAPSIM, a tool that automatically generates multiagent
simulations from formal multiagent planning (MAP) domains. For different
such simulations, we show how CCP leads to collaborative planning
and acting and, despite minimal linguistic capabilities, to fairly
natural dialogues between agents. },
DATE-ADDED = {2009-01-07 17:04:37 +0000},
DATE-MODIFIED = {2009-01-07 17:24:27 +0000},
URL = {http://www.cognitivesystems.org/publications/brenner-aamas08.pdf}
}
@INPROCEEDINGS{Brenner:2007a,
AUTHOR = {Michael Brenner},
TITLE = {Situation-Aware Interpretation, Planning and Execution of User Commands
by Autonomous Robots},
BOOKTITLE = {Proceedings of IEEE RO-MAN 2007},
YEAR = {2007},
ABSTRACT = { For a robot to be able to first understand and then achieve a human's
goals, it must be able to reason about a) the context of the current
situation (with respect to which it must interpret the human's commands)
and b) the future world state (as intended by the human) and how
to achieve it. Since humans express their intentions and plans using
qualitative symbolic representations, robots must be enabled to reason
and interact on the same representational level. In this paper, we
describe the use of classical AI Planning techniques for situation-aware
interpretation and execution of human commands. We show how, based
on a Planning domain, a robot can be enabled to understand commands
in natural language, plan for their situation-dependent realization
and revise its plans based on new perceptions. We show the effectiveness
of this approach in several HRI scenarios modeled as Planning domains
as well as with examples from a real robot system developed in the
EU-funded CoSy project. },
DATE-ADDED = {2009-01-07 17:04:37 +0000},
DATE-MODIFIED = {2009-01-07 17:25:11 +0000},
LOCATION = {Jeju, Korea},
URL = {http://www.cognitivesystems.org/publications/brenner-roman07.pdf}
}
@INPROCEEDINGS{Brenner/etal:2008a,
AUTHOR = {Michael Brenner and Ivana Kruijff-Korbayov\'a},
TITLE = {A Continual Multiagent Planning Approach to Situated Dialogue},
BOOKTITLE = {Proceedings of the 12th Workshop on the Semantics and Pragmatics
of Dialogue (Semdial)},
YEAR = {2008},
ADDRESS = {London, UK},
ABSTRACT = {Situated dialogue is usually tightly integrated with behavior planning,
physical action and perception. This paper presents an algorithmic
framework, Continual Collaborative Planning (CCP), for modeling this
kind of integrated behavior and shows how CCP agents naturally blend
physical and communicative actions. For experiments with conversational
CCP agents we have developed MAPSIM, a software environment that
can generate multiagent simulations from formal multiagent planning
problems automatically. MAPSIM permits comparison of CCP-based dialogue
strategies on a wide range of domains and problems without domain-specific
programming. Despite their linguistic capabilities being limited
MAPSIM agents can already engage in fairly realistic situated dialogues.
},
DATE-ADDED = {2009-01-07 17:04:37 +0000},
DATE-MODIFIED = {2009-01-07 17:24:22 +0000},
URL = {http://www.cognitivesystems.org/publications/londial08.pdf}
}
@ARTICLE{Brenner/etal:2008,
AUTHOR = {Michael Brenner and Bernhard Nebel},
TITLE = {Continual Planning and Acting in Dynamic Multiagent Environments},
JOURNAL = {Journal of Autonomous Agents and Multiagent Systems},
YEAR = {To appear},
NOTE = {accepted for publication},
ABSTRACT = {In highly dynamic environments, e.g. multiagent systems, finding optimal
action plans is practically impossible since individual agents lack
important knowledge at planning time or this knowledge has become
obsolete when a plan is executed. It is often more practical in such
environments to enable agents to actively extend their knowledge
as part of their plans and then revise their decisions in light of
these update. In this paper, we describe a new principled approach
to Continual Planning, i.e. the integration of Planning, Execution
and Monitoring. The algorithm deliberately postpones parts of the
planning process to later stages in an agent's plan-act-monitor cycle
and automatically determines when to switch back to refining or revising
a partly executed plan. To evaluate our (and others') Continual Planning
techniques we have developed a simulation environment where formal
MA Planning domains are not only used by planning agents but also
as the basis of the simulation model such that agents can not only
plan, but execute actions and perceive their environment. Our experiments
show that, using continual planning techniques, deliberate action
planning can be used efficiently even in complex multiagent environments.},
DATE-ADDED = {2009-01-07 17:04:37 +0000},
DATE-MODIFIED = {2009-01-07 17:24:37 +0000}
}
@INPROCEEDINGS{Brenner/etal:2006a,
AUTHOR = {Michael Brenner and Bernhard Nebel},
TITLE = {Continual planning and acting in dynamic multiagent environments},
BOOKTITLE = {PCAR '06: Proceedings of the 2006 international symposium on Practical
cognitive agents and robots},
YEAR = {2006},
PAGES = {15--26},
ADDRESS = {New York, NY, USA},
PUBLISHER = {ACM},
DATE-ADDED = {2009-01-07 17:19:44 +0000},
DATE-MODIFIED = {2009-01-07 17:24:31 +0000},
DOI = {http://doi.acm.org/10.1145/1232425.1232431},
ISBN = {1-74052-130-7},
LOCATION = {Perth, Australia},
URL = {http://www.cognitivesystems.org/publications/brenner-nebel06.pdf}
}
@INPROCEEDINGS{Kruijff/Brenner:2007,
AUTHOR = {Kruijff, G.J.M. and Brenner, M},
TITLE = {Modelling Spatio-Temporal Comprehension in Situated Human-Robot Dialogue
as Reasoning about Intentions and Plans},
BOOKTITLE = {Proceedings of the Symposium on Intentions in Intelligent Systems,
AAAI Spring Symposium Series 2007},
YEAR = {2007},
ADDRESS = {Stanford University, Palo Alto, CA},
MONTH = {March},
ABSTRACT = {The article presents a cross-modal approach to modeling spatio-temporal
comprehension in situated dialogue. The article proposes an approach
for representing spatiotemporal-causal structure at the level of
linguistically conveyed meaning, adopting the notion of event nucleus
presented \cite{Steedman:POT}. In the approach, basic tense, aspect
and modality can be captured, as well as aspectual coercion, and
temporal sequencing. The article then discusses how the incremental
construction of such linguistic representations can be combined with
continuous action planning. Through cross-modal integration of action
planning representations into linguistic processing, the article
explores how action planning can prime selectional attention in utterance
comprehension by disambiguating linguistic analyses on the basis
of plan availability, and by raising expectations what action(s)
may be talked about next. Furthermore, planning can complement linguistic
analyses with information about spatiotemporal-causal structure established
in planning inferences. This makes such inferences available for
future referencing in the discourse context, yet lessening the load
on dialogue comprehension for having to establish them.},
URL = {http://www.cognitivesystems.org/publications/SS03KruijffG.pdf}
}
@INPROCEEDINGS{Plagemann/etal:2006,
AUTHOR = {Plagemann, C. and Stachniss, C. and Burgard, W.},
TITLE = {Efficient Failure Detection for Mobile Robots using Mixed-Abstraction
Particle Filters},
BOOKTITLE = {European Robotics Symposium 2006},
YEAR = {2006},
EDITOR = {H.I. Christiensen},
VOLUME = {22},
SERIES = {STAR Springer tracts in advanced robotics},
PAGES = {93--107},
PUBLISHER = {Springer-Verlag Berlin Heidelberg, Germany},
ABSTRACT = {In this paper, we consider the problem of online failure detection
and isolation for mobile robots. The goal is to enable a mobile robot
to determine whether the system is running free of faults or to identify
the cause for faulty behavior. In general, failures cannot be detected
by solely monitoring the process model for the error free mode because
if certain model assumptions are violated the observation likelihood
might not indicate a defect. Existing approaches therefore use comparably
complex system models to cover all possible system behaviors. In
this paper, we propose the mixed-abstraction particle lter as an
efcient way of dealing with potential failures of mobile robots.
It uses a hierarchy of process models to actively validate the model
assumptions and distribute the computational resources between the
models adaptively. We present an implementation of our algorithm
and discuss results obtained from simulated and real-robot experiments.},
DATE-ADDED = {2009-01-07 17:04:50 +0000},
DATE-MODIFIED = {2009-01-07 17:27:30 +0000},
ISBN = {3-540-32688-X},
PDFURL = {http://www.cognitivesystems.org/publications/plagemann06euros.pdf},
URL = {http://www.cognitivesystems.org/publications/plagemann06euros.pdf}
}
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