19 Search Results for "Lakemeyer, Gerhard"


Document
Cognitive Robotics (Dagstuhl Seminar 22391)

Authors: Fredrik Heintz, Gerhard Lakemeyer, and Sheila McIlraith

Published in: Dagstuhl Reports, Volume 12, Issue 9 (2023)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 22391 on the topic of "Cognitive Robotics". Cognitive Robotics is concerned with endowing robots or software agents with higher level cognitive functions that involve reasoning, for example, about goals, perception, actions, the mental states of other agents, and collaborative task execution. The seminar is the latest event in a series of events on this topic that were initiated in 1998. With its roots in knowledge representation and reasoning, the program for this seminar was influenced by transformative advances in machine learning and deep learning, by recent advances in human-robot interactions, and by issues that arise in the development of trustworthy cognitive robotic systems. Reflective of this, the seminar featured sessions devoted to the following four themes: cognitive robotics and KR, verification of cognitive robots, human-robot interaction and robot ethics, and planning and learning. Each theme consisted of plenary talks, plenary discussions and working groups resulting in a research road map for the coming years. There was also a poster session where new or published results could be presented by the participants. The seminar was very successful and well received by the participants thanks to the excellent environment for exchanging ideas provided by Schloss Dagstuhl.

Cite as

Fredrik Heintz, Gerhard Lakemeyer, and Sheila McIlraith. Cognitive Robotics (Dagstuhl Seminar 22391). In Dagstuhl Reports, Volume 12, Issue 9, pp. 200-219, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@Article{heintz_et_al:DagRep.12.9.200,
  author =	{Heintz, Fredrik and Lakemeyer, Gerhard and McIlraith, Sheila},
  title =	{{Cognitive Robotics (Dagstuhl Seminar 22391)}},
  pages =	{200--219},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{12},
  number =	{9},
  editor =	{Heintz, Fredrik and Lakemeyer, Gerhard and McIlraith, Sheila},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.12.9.200},
  URN =		{urn:nbn:de:0030-drops-178132},
  doi =		{10.4230/DagRep.12.9.200},
  annote =	{Keywords: Artificial Intelligence, Knowledge Representation and Reasoning, Cognitive Robotics, Verification, Human-robot Interaction, Robot Ethics, Machine Learning, Planning}
}
Document
Planning with epistemic goals (Dagstuhl Seminar 14032)

Authors: Thomas Agotnes, Gerhard Lakemeyer, Benedikt Löwe, and Bernhard Nebel

Published in: Dagstuhl Reports, Volume 4, Issue 1 (2014)


Abstract
This report documents the outcomes of Dagstuhl Seminar 14032 "Planning with epistemic goals". It brought together the communities of so far relatively separate research areas related to artificial intelligence and logic: automated planning on the one hand, and dynamic logics of interaction on the other. Significant overlap in motivation, theory and methods was discovered, and a good potential for cross fertilization became apparent.

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Thomas Agotnes, Gerhard Lakemeyer, Benedikt Löwe, and Bernhard Nebel. Planning with epistemic goals (Dagstuhl Seminar 14032). In Dagstuhl Reports, Volume 4, Issue 1, pp. 83-103, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@Article{agotnes_et_al:DagRep.4.1.83,
  author =	{Agotnes, Thomas and Lakemeyer, Gerhard and L\"{o}we, Benedikt and Nebel, Bernhard},
  title =	{{Planning with epistemic goals (Dagstuhl Seminar 14032)}},
  pages =	{83--103},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{4},
  number =	{1},
  editor =	{Agotnes, Thomas and Lakemeyer, Gerhard and L\"{o}we, Benedikt and Nebel, Bernhard},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.4.1.83},
  URN =		{urn:nbn:de:0030-drops-45369},
  doi =		{10.4230/DagRep.4.1.83},
  annote =	{Keywords: planning, epistemic logic, modal logic}
}
Document
Robot Learning Constrained by Planning and Reasoning

Authors: Claude Sammut, Raymond Sheh, and Tak Fai Yi

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Robot learning is usually done by trial-anderror or learning by example. Neither of these methods takes advantage of prior knowledge or of any ability to reason about actions. We describe two learning systems. In the first, we learn a model of a robot's actions. This is used in simulation to search for a sequence of actions that achieves the goal of traversing rough terrain. Further learning is used to compress the results of this search into a set of situation-action rules. In the second system, we assume the robot has some knowledge of the effects of actions and can use these to plan a sequence of actions. The qualitative states that result from the plan are used as constraints for trial-and-error learning. This approach greatly reduces the number of trials required by the learner. The method is demonstrated on the problem of a bipedal robot learning to walk.

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Claude Sammut, Raymond Sheh, and Tak Fai Yi. Robot Learning Constrained by Planning and Reasoning. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{sammut_et_al:DagSemProc.10081.14,
  author =	{Sammut, Claude and Sheh, Raymond and Yi, Tak Fai},
  title =	{{Robot Learning Constrained by Planning and Reasoning}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.14},
  URN =		{urn:nbn:de:0030-drops-28163},
  doi =		{10.4230/DagSemProc.10081.14},
  annote =	{Keywords: }
}
Document
10081 Abstracts Collection – Cognitive Robotics

Authors: Gerhard Lakemeyer, Hector J. Levesque, and Fiora Pirri

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
From 21.02. to 26.02.2010, the Dagstuhl Seminar 10081 ``Cognitive Robotics '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

Cite as

Gerhard Lakemeyer, Hector J. Levesque, and Fiora Pirri. 10081 Abstracts Collection – Cognitive Robotics. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{lakemeyer_et_al:DagSemProc.10081.1,
  author =	{Lakemeyer, Gerhard and Levesque, Hector J. and Pirri, Fiora},
  title =	{{10081 Abstracts Collection – Cognitive Robotics}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--19},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.1},
  URN =		{urn:nbn:de:0030-drops-27776},
  doi =		{10.4230/DagSemProc.10081.1},
  annote =	{Keywords: Cognitive roboticsm, Knowledge representation and reasoning, Machine learning, Cognitive science, Cognitive vision}
}
Document
A Constraint-Based Approach for Plan Management in Intelligent Environments

Authors: Federico Pecora and Marcello Cirillo

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
In this paper we address the problem of realizing a service-providing reasoning infrastructure for proactive human assistance in intelligent environments. We propose SAM, an architecture which leverages temporal knowledge represented as relations in Allen’s interval algebra and constraint-based temporal planning techniques. SAM seamlessly combines two key capabilities for contextualized service provision, namely human activity recognition and planning for controlling pervasive actuation devices.

Cite as

Federico Pecora and Marcello Cirillo. A Constraint-Based Approach for Plan Management in Intelligent Environments. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{pecora_et_al:DagSemProc.10081.2,
  author =	{Pecora, Federico and Cirillo, Marcello},
  title =	{{A Constraint-Based Approach for Plan Management in Intelligent Environments}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.2},
  URN =		{urn:nbn:de:0030-drops-26358},
  doi =		{10.4230/DagSemProc.10081.2},
  annote =	{Keywords: }
}
Document
Attending to Motion: an object-based approach

Authors: Anna Belardinelli

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Visual attention is the biological mechanism allowing to turn mere sensing into conscious perception. In this process, object-based modulation of attention provides a further layer between low-level space/feature-based region selection and full object recognition. In this context, motion is a very powerful feature, naturally attracting our gaze and yielding rapid and effective shape distinction. Moving from a pixel-based account of attention to the definition of proto-objects as perceptual units labelled with a single saliency value, we present a framework for the selection of moving objects within cluttered scenes. Through segmentation of motion energy features, the system extracts coherently moving proto-objects defining them as consistently moving blobs and produces an object saliency map, by evaluating bottom-up distinctiveness of each object candidate with respect to its surroundings, in a center-surround fashion.

Cite as

Anna Belardinelli. Attending to Motion: an object-based approach. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{belardinelli:DagSemProc.10081.3,
  author =	{Belardinelli, Anna},
  title =	{{Attending to Motion: an object-based approach}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.3},
  URN =		{urn:nbn:de:0030-drops-26285},
  doi =		{10.4230/DagSemProc.10081.3},
  annote =	{Keywords: Visual attention model, motion selection, saliency map}
}
Document
Attentive Monitoring and Adaptive Control in Cognitive Robotics

Authors: E. Burattini, Alberto Finzi, S. Rossi, and Maria Carla Staffa

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
In this work, we present an attentional system for a robotic agent capable of adapting its emergent behavior to the surrounding environment and to its internal state. In this framework, the agent is endowed with simple attentional mechanisms regulating the frequencies of sensory readings and behavior activations. The process of changing the frequency of sensory readings is interpreted as an increase or decrease of attention towards relevant behaviors and particular aspects of the external environment. In this paper, we present our framework discussing several case studies considering incrementally complex behaviors and tasks.

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E. Burattini, Alberto Finzi, S. Rossi, and Maria Carla Staffa. Attentive Monitoring and Adaptive Control in Cognitive Robotics. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{burattini_et_al:DagSemProc.10081.4,
  author =	{Burattini, E. and Finzi, Alberto and Rossi, S. and Staffa, Maria Carla},
  title =	{{Attentive Monitoring and Adaptive Control in Cognitive Robotics}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.4},
  URN =		{urn:nbn:de:0030-drops-26322},
  doi =		{10.4230/DagSemProc.10081.4},
  annote =	{Keywords: Attention, behavior-based control, robotics}
}
Document
Cognitive Robotics

Authors: Hector J. Levesque and Gerhard Lakemeyer

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
This chapter is dedicated to the memory of Ray Reiter. It is also an overview of cognitive robotics, as we understand it to have been envisaged by him.1 Of course, nobody can control the use of a term or the direction of research. We apologize in advance to those who feel that other approaches to cognitive robotics and related problems are inadequately represented here.

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Hector J. Levesque and Gerhard Lakemeyer. Cognitive Robotics. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{levesque_et_al:DagSemProc.10081.5,
  author =	{Levesque, Hector J. and Lakemeyer, Gerhard},
  title =	{{Cognitive Robotics}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--19},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.5},
  URN =		{urn:nbn:de:0030-drops-26335},
  doi =		{10.4230/DagSemProc.10081.5},
  annote =	{Keywords: }
}
Document
Combining Planning and Motion Planning

Authors: Jaesik Choi and Eyal Amir

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Robotic manipulation is important for real, physical world applications. General Purpose manipulation with a robot (eg. delivering dishes, opening doors with a key, etc.) is demanding. It is hard because (1) objects are constrained in position and orientation, (2) many non-spatial constraints interact (or interfere) with each other, and (3) robots may have multidegree of freedoms (DOF). In this paper we solve the problem of general purpose robotic manipulation using a novel combination of planning and motion planning. Our approach integrates motions of a robot with other (non-physical or external-to-robot) actions to achieve a goal while manipulating objects. It differs from previous, hierarchical approaches in that (a) it considers kinematic constraints in configuration space (C-space) together with constraints over object manipulations; (b) it automatically generates high-level (logical) actions from a C-space based motion planning algorithm; and (c) it decomposes a planning problem into small segments, thus reducing the complexity of planning.

Cite as

Jaesik Choi and Eyal Amir. Combining Planning and Motion Planning. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{choi_et_al:DagSemProc.10081.6,
  author =	{Choi, Jaesik and Amir, Eyal},
  title =	{{Combining Planning and Motion Planning}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.6},
  URN =		{urn:nbn:de:0030-drops-26294},
  doi =		{10.4230/DagSemProc.10081.6},
  annote =	{Keywords: Motion Planning, Factored Planning, Robotic arm}
}
Document
Coming up With Good Excuses: What to do When no Plan Can be Found

Authors: Moritz Göbeldecker, Thomas Keller, Patrick Eyerich, Michael Brenner, and Bernhard Nebel

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
can go wrong. First and foremost, an agent might fail to execute one of the planned actions for some reasons. Even more annoying, however, is a situation where the agent is incompetent, i.e., unable to come up with a plan. This might be due to the fact that there are principal reasons that prohibit a successful plan or simply because the task’s description is incomplete or incorrect. In either case, an explanation for such a failure would be very helpful. We will address this problem and provide a formalization of coming up with excuses for not being able to find a plan. Based on that, we will present an algorithm that is able to find excuses and demonstrate that such excuses can be found in practical settings in reasonable time.

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Moritz Göbeldecker, Thomas Keller, Patrick Eyerich, Michael Brenner, and Bernhard Nebel. Coming up With Good Excuses: What to do When no Plan Can be Found. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{gobeldecker_et_al:DagSemProc.10081.7,
  author =	{G\"{o}beldecker, Moritz and Keller, Thomas and Eyerich, Patrick and Brenner, Michael and Nebel, Bernhard},
  title =	{{Coming up With Good Excuses: What to do When no Plan Can be Found}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.7},
  URN =		{urn:nbn:de:0030-drops-27739},
  doi =		{10.4230/DagSemProc.10081.7},
  annote =	{Keywords: Planning, knowledge representation}
}
Document
Exploiting Spatial and Temporal Flexibility for Exploiting Spatial and Temporal Flexibility for Plan Execution of Hybrid, Under-actuated Systems

Authors: Andreas G. Hofmann and Brian C. Williams

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Robotic devices, such as rovers and autonomous spacecraft, have been successfully controlled by plan execution systems that use plans with temporal flexibility to dynamically adapt to temporal disturbances. To date these execution systems apply to discrete systems that abstract away the detailed dynamic constraints of the controlled device. To control dynamic, under-actuated devices, such as agile bipedal walking machines, we extend this execution paradigm to incorporate detailed dynamic constraints. Building upon prior work on dispatchable plan execution, we introduce a novel approach to flexible plan execution of hybrid under-actuated systems that achieves robustness by exploiting spatial as well as temporal plan flexibility. To accomplish this, we first transform the high-dimensional system into a set of low dimensional, weakly coupled systems. Second, to coordinate these systems such that they achieve the plan in real-time, we compile a plan into a concurrent timed flow tube description. This description represents all feasible control trajectories and their temporal coordination constraints, such that each trajectory satisfies all plan and dynamic constraints. Finally, the problem of runtime plan dispatching is reduced to maintaining state trajectories in their associated flow tubes, while satisfying the coordination constraints. This is accomplished through an efficient local search algorithm that adjusts a small number of control parameters in real-time. The first step has been published previously; this paper focuses on the last two steps. The approach is validated on the execution of a set of bipedal walking plans, using a high fidelity simulation of a biped.

Cite as

Andreas G. Hofmann and Brian C. Williams. Exploiting Spatial and Temporal Flexibility for Exploiting Spatial and Temporal Flexibility for Plan Execution of Hybrid, Under-actuated Systems. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{hofmann_et_al:DagSemProc.10081.8,
  author =	{Hofmann, Andreas G. and Williams, Brian C.},
  title =	{{Exploiting Spatial and Temporal Flexibility for Exploiting Spatial and Temporal Flexibility for Plan Execution of Hybrid, Under-actuated Systems}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.8},
  URN =		{urn:nbn:de:0030-drops-27740},
  doi =		{10.4230/DagSemProc.10081.8},
  annote =	{Keywords: }
}
Document
golog.lua: Towards a Non-Prolog Implementation of Golog for Embedded Systems

Authors: Alexander Ferrein

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Among many approaches to address the high-level decision making problem for autonomous robots and agents, the robot program¬ming and plan language Golog follows a logic-based deliberative approach, and its successors were successfully deployed in a number of robotics applications over the past ten years. Usually, Golog interpreter are implemented in Prolog, which is not available for our target plat¬form, the bi-ped robot platform Nao. In this paper we sketch our first approach towards a prototype implementation of a Golog interpreter in the scripting language Lua. With the example of the elevator domain we discuss how the basic action theory is specified and how we implemented fluent regression in Lua. One possible advantage of the availability of a Non-Prolog implementation of Golog could be that Golog becomes avail¬able on a larger number of platforms, and also becomes more attractive for roboticists outside the Cognitive Robotics community.

Cite as

Alexander Ferrein. golog.lua: Towards a Non-Prolog Implementation of Golog for Embedded Systems. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{ferrein:DagSemProc.10081.9,
  author =	{Ferrein, Alexander},
  title =	{{golog.lua: Towards a Non-Prolog Implementation of Golog for Embedded Systems}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.9},
  URN =		{urn:nbn:de:0030-drops-26317},
  doi =		{10.4230/DagSemProc.10081.9},
  annote =	{Keywords: Action and change, high-level control, robotics}
}
Document
Improving the Performance of Complex Agent Plans Through Reinforcement Learning

Authors: Matteo Leonetti and Luca Iocchi

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Agent programming in complex, partially observable, and stochastic domains usually requires a great deal of understanding of both the domain and the task in order to provide the agent with the knowledge necessary to act effectively. While symbolic methods allow the designer to specify declarative knowledge about the domain, the resulting plan can be brittle since it is difficult to supply a symbolic model that is accurate enough to foresee all possible events in complex environments, especially in the case of partial observability. Reinforcement Learning (RL) techniques, on the other hand, can learn a policy and make use of a learned model, but it is difficult to reduce and shape the scope of the learning algorithm by exploiting a priori information. We propose a methodology for writing complex agent programs that can be effectively improved through experience.We show how to derive a stochastic process from a partial specification of the plan, so that the latter’s perfomance can be improved solving a RL problem much smaller than classical RL formulations. Finally, we demonstrate our approach in the context of Keepaway Soccer, a common RL benchmark based on a RoboCup Soccer 2D simulator.

Cite as

Matteo Leonetti and Luca Iocchi. Improving the Performance of Complex Agent Plans Through Reinforcement Learning. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{leonetti_et_al:DagSemProc.10081.10,
  author =	{Leonetti, Matteo and Iocchi, Luca},
  title =	{{Improving the Performance of Complex Agent Plans Through Reinforcement Learning}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.10},
  URN =		{urn:nbn:de:0030-drops-26347},
  doi =		{10.4230/DagSemProc.10081.10},
  annote =	{Keywords: Agent programming, planning, reinforcement learning, semi non-Markov decision process}
}
Document
Modeling the Observed Behavior of a Robot through Machine Learning

Authors: Malik Ghallab

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
Artificial systems are becoming more and more complex, almost as complex in some cases as natural systems. Up to now, the typical engineering question was "how do I design my system to behave according to some specifications". However, the incremental design process is leading to so complex artifacts that engineers are more and more addressing a quite different issue of "how do I model the observed behavior of my system". Engineers are faced with the same problem as scientists studying natural phenomena. It may sound strange for an engineer to engage in observing and modeling what a system is doing, since this should be inferable from the models used in the system's design stage. However, a modular design of a complex artifact develops only local models that are combined on the basis of some composition principle of these models; it seldom provides global behavior models.

Cite as

Malik Ghallab. Modeling the Observed Behavior of a Robot through Machine Learning. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, p. 1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


Copy BibTex To Clipboard

@InProceedings{ghallab:DagSemProc.10081.11,
  author =	{Ghallab, Malik},
  title =	{{Modeling the Observed Behavior of a Robot through Machine Learning}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--1},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.11},
  URN =		{urn:nbn:de:0030-drops-26379},
  doi =		{10.4230/DagSemProc.10081.11},
  annote =	{Keywords: Robotics, Machine Learning}
}
Document
On First-Order Definability and Computability of Progression for Local-Effect Actions and Beyond

Authors: Yongmei Liu and Gerhard Lakemeyer

Published in: Dagstuhl Seminar Proceedings, Volume 10081, Cognitive Robotics (2010)


Abstract
In a seminal paper, Lin and Reiter introduced the notion of progression for basic action theories in the situation calculus. Unfortunately, progression is not first-order definable in general. Recently, Vassos, Lakemeyer, and Levesque showed that in case actions have only local effects, progression is firstorder representable. However, they could show computability of the first-order representation only for a restricted class. Also, their proofs were quite involved. In this paper, we present a result stronger than theirs that for local-effect actions, progression is always first-order definable and computable. We give a very simple proof for this via the concept of forgetting. We also show first-order definability and computability results for a class of knowledge bases and actions with non-local effects. Moreover, for a certain class of local-effect actions and knowledge bases for representing disjunctive information, we show that progression is not only firstorder definable but also efficiently computable.

Cite as

Yongmei Liu and Gerhard Lakemeyer. On First-Order Definability and Computability of Progression for Local-Effect Actions and Beyond. In Cognitive Robotics. Dagstuhl Seminar Proceedings, Volume 10081, pp. 1-7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


Copy BibTex To Clipboard

@InProceedings{liu_et_al:DagSemProc.10081.12,
  author =	{Liu, Yongmei and Lakemeyer, Gerhard},
  title =	{{On First-Order Definability and Computability of Progression for Local-Effect Actions and Beyond}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--7},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10081.12},
  URN =		{urn:nbn:de:0030-drops-26380},
  doi =		{10.4230/DagSemProc.10081.12},
  annote =	{Keywords: Action and change, knowledge representation}
}
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