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News Journal onPlanning and Scheduling |
| Vol.4, No.2 | Editor: Susanne Biundo | July 4, 2000 |
Editorial |
New Submission Arrived | ||
| International Summer School on AI Planning | |||
Articles |
How to Submit | ||
| Received Research Articles | |||
| Accepted Research Articles | |||
Debates |
Debates About Current Research Articles | ||
Events |
Conferences | ||
| Workshops | |||
| Tutorials | |||
Jobs |
Job Announcements | ||
New Papers |
Recent Publications | ||
Previous Issues |
Previous Issues of this News Journal | ||
Editorial |
I am happy to announce a new submission: Causal Models for Concurrent Reactive Robot Action Plans by Michael Beetz and Henrik Grosskreutz. The paper is open to public online discussion for a period of three months. You are invited to send in your questions and comments via the paper's discussion page. The authors are looking forward to receiving your feedback!
The papers that have been submitted to the special track on "Planning and Scheduling in Dynamic and Uncertain Environments" have now entered into the confidential refereeing process. However, there is still a chance to contribute to the discussion. Please enter the special track section to access the papers and the respective discussion pages.
The International Summer School on AI Planning will be held from
September 28 to October 1 at Cyprus. The application deadline is July
14. The school is organised by Maria Fox, Alfonso Gerevini, and Yannis Dimopoulos. Detailed
information about the school and about funding opportunities can be found
here.
The school is sponsored by PLANET
and by IJCAI.
Finally, I am looking forward - as always - to receive paper submissions as well as announcements and other relevant information for publication in the News Journal and the Electronic Colloquium.
Susanne Biundo
(area editor)
Articles and Debates |
Received Research Articles on Planning and Scheduling |
Michael Beetz, Henrik Grosskreutz
Causal Models for Concurrent Reactive Robot
Action Plans
Abstract:
Temporal projection, the process of predicting what will happen when a
robot executes its plan, is essential for autonomous service robots to
successfully plan their missions. This paper describes a causal model of
the behavior exhibited by a mobile robot when running concurrent
reactive plans. The model represents aspects of robot behavior that
cannot be represented by most action models used in AI planning: it
represents the temporal structure of continuous control processes,
several modes of their interferences, and various kinds of uncertainty.
This enhanced expressiveness enables robot action planning systems to
predict, and therefore forestall, various kinds of behavior flaws
including missed deadlines whilst expoiting incidental opportunities.
the proposed causal model is experimentally validated.
Date of Submission: May 23, 2000
Special Track on
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Abdel-Illah Mouaddib
Multi-Criteria Decision Quality Optimization as a Scheduling Problem
Abstract:
Decision quality under uncertainty is a problem that has been addressed
by many researchers. But most of the works dedicated to this problem
assume that there is a single quality measure to computation based on
the status of an n-tuple of criteria. However, in most of real-world
applications the quality is multi-criteria where each criterion captures
a dimension of value in the solution. In this paper, we present a
decision maker that manipulates the quality as a vector of criteria
where the improvemnet of each criterion is in charge of a progressive
processing agent that uses its hierarchy of processing levels to improve
the quality of this criterion incrementally. We discuss the problem of
optimizing the decision of sequencing processing levels of agents by
transforming it to a MDP. We also present the strategy to be adopted
when considering the criteria preferences. Finally, we discuss how this
approach can be applied to controlling a static set of dependent
progressive processing agents where there is no predetermined sequence
of agents.
Date of Submission: March 7, 2000
Tara Estlin, Gregg Rabideau, Darren Mutz, Steve Chien
Using Continuous Planning Techniques to Coordinate Multiple Rovers
Abstract:
This paper describes a dynamic planning system for coordinating
multiple rovers in collecting planetary surface data. A distributed
planning system is shown to generate rover plans for achieving science
goals, coordinate activities among rovers, monitor plan execution, and
perform re-planning when necessary. Specifically, we describe how
rover command generation can be automated to help relieve some of the
burden on human operators. We describe the issues inherent in planning
for a distributed set of rovers and discuss how these issues can be
addressed in a dynamic and uncertain environment. Finally, we describe
a prototype system for automatically generating low-level commands and
monitoring their execution for a team of rovers with the overall goal
of achieving a set of geology-related science requests.
Date of Submission: February 9, 2000
Richard Washington, Keith Golden, John Bresina
Plan Execution, Monitoring, and Adaptation for Planetary Rovers
Abstract:
Planetary rovers must perform their missions in unknown environments
with limited communication to ground controllers. To endow a rover with
the capability for robust autonomous operation, we have designed an
on-board executive architecture that incorporates robust flexible
operation, monitoring of system and environmental state, and limited
plan adaptation. The rover executive receives a plan with flexible time
and resource contraints along with local and global contingency plans to
handle deviations from the nominal plan. It internally monitors plan
execution for communication and execution failures; through sensors and
models of its operation it determines its internal state, its resource
usage, and its interaction with respect to the environment. Based on the
information it gathers from the sonsors, it chooses the most appropriate
course of action, potentially inserting contingency plans into its
current plan, thus adapting its plan to fit the current situation.
Date of Submission: February 17, 2000
Massimo Paolucci, Onn Shehory, Katia Sycara
Interleaving
Planning and Execution in a Multiagent Team Planning Environment
Abstract:
Agents in a multiagent system may need to share information and
services. For this, they need to be able to interleave deliberative
planning with execution of actions. The deliberative planning is needed
to decide which actions to perform to achieve an objective, whereas
execution of some of the actions is needed to make a more informed
decision on the other actions and to access services provided by other
agents.
HITaP is a planner that interleaves planning and execution: using HITaP
an agent can, during planning, gather information by either direct
inspection of the domain or by firing queries to other agents and
recording their answers. Interleaving planning and execution, as
provided by HITaP, plays a crucial role in an agent's ability to
construct shared plans with other agents and to manage the negotiation
process that leads to agreement with the agent's teammates on these
plans.
HITaP is implemented and currently used as planning module for agents in
the RETSINA multiagent system. These agents cooperate to solve problems
in different domains that range from portfolio management to command and
control decision support systems.
Date of Submission: February 5, 2000
Debates About Received Articles |
Michael Beetz, Henrik Grosskreutz
Causal Models for Concurrent Reactive Robot Action
Plans
Abdel-Illah Mouaddib
Multi-Criteria Decision Quality Optimization as a Scheduling Problem
Tara Estlin, Gregg Rabideau, Darren Mutz, Steve Chien
Using Continuous Planning Techniques to Coordinate Multiple Rovers
Richard Washington, Keith Golden, John Bresina
Plan Execution, Monitoring, and Adaptation for Planetary Rovers
Massimo Paolucci, Onn Shehory, Katia Sycara
Interleaving Planning and Execution in a Multiagent Team Planning
Environment
Accepted Research Articles on Planning and Scheduling |
The following articles, which have previously been received, have been accepted by the ETAI after confidential review, thereby achieving proof of high journal quality.
Please click here for a list of all accepted articles.
Events |
SARA2000: Symposium on Abstraction, Reformulation and Approximation.
The conference will be held from July 26 to 29 in Lake LBJ, Texas,
USA.
AAAI-2000: Seventeenth National Conference on Artificial Intelligence.
The conference will be held from July 30 to August 3 in Austin, Texas, USA.
ECAI-2000: Fourteenth European Conference on Artificial Intelligence.
The conference will be held from August 20 to 29 in Berlin, Germany.
IJCAI-2001:
Seventeenth International Joint Conference on Artificial Intelligence.
The conference will be held from August 4 to 10 in Seattle,
Washington, USA.
Workshop and Tutorial Proposal Submission Deadline:
October 1, 2000.
Paper Submission Deadline:
January 8, 2001.
ECP2001: Sixth
European Conference on Planning.
The conference will be held in September in Spain.
New Results in Planning, Scheduling, and Design, organised by Jürgen Sauer, to be held in conjunction with ECAI-2000 on August 21 and 22 in Berlin, Germany.
Jobs |
This section provides current offers as well as access to sites where relevant jobs are regularly announced. It invites your submissions.
Many job offers in planning, scheduling, and constraint reasoning can be found on this page.
Job openings at the Artificial Intelligence Applications Institute (AIAI) at the University of Edinburgh are always announced on this page. They include occasional positions and studentships in the Knowledge-Based Planning Group at AIAI.
New Papers |
Last update: July 4, 2000
Administrated by
Susanne Biundo,
University of Ulm, Germany.
biundo@informatik.uni-ulm.de.