Results 1 - 10
of
120
Experiences with an Architecture for Intelligent, Reactive Agents
"... This paper describes an implementation of the 3T robot architecture which has been under development for the last eightyears. The architecture uses three levels of abstraction and description languages whichare compatible between levels. The makeup of the architecture helps to coordinate planful ..."
Abstract
-
Cited by 360 (31 self)
- Add to MetaCart
(Show Context)
This paper describes an implementation of the 3T robot architecture which has been under development for the last eightyears. The architecture uses three levels of abstraction and description languages whichare compatible between levels. The makeup of the architecture helps to coordinate planful activities with real-time behaviors for dealing with dynamic environments. In recent years, other architectures have been created with similar attributes but two features distinguish the 3T architecture: 1) a variety of useful software tools have been created to help implement this architecture on multiple real robots;, and 2) this architecture, or parts of it, have been implemented on a varietyofvery different robot systems using different processors, operating systems, effectors and sensor suites.
EXACT AND APPROXIMATE ALGORITHMS FOR PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES
, 1998
"... Automated sequential decision making is crucial in many contexts. In the face of uncertainty, this task becomes even more important, though at the same time, computing optimal decision policies becomes more complex. The more sources of uncertainty there are, the harder the problem becomes to solve. ..."
Abstract
-
Cited by 186 (2 self)
- Add to MetaCart
Automated sequential decision making is crucial in many contexts. In the face of uncertainty, this task becomes even more important, though at the same time, computing optimal decision policies becomes more complex. The more sources of uncertainty there are, the harder the problem becomes to solve. In this work, we look at sequential decision making in environments where the actions have probabilistic outcomes and in which the system state is only partially observable. We focus on using a model called a partially observable Markov decision process (POMDP) and explore algorithms which address computing both optimal and approximate policies for use in controlling processes that are modeled using POMDPs. Although solving for the optimal policy is PSPACE-complete (or worse), the study and improvements of exact algorithms lends insight into the optimal solution structure as well as providing a basis for approximate solutions. We present some improvements, analysis and empirical comparisons for some existing and some novel approaches for computing the optimal POMDP policy exactly. Since it is also hard (NP-complete or worse) to derive close approximations to the optimal solution for POMDPs, we consider a number of approaches for deriving policies that yield sub-optimal control and empirically explore their performance on a range of problems. These approaches
Intelligence by Design: Principles of Modularity and Coordination for Engineering Complex Adaptive Agents
, 2001
"... All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. T ..."
Abstract
-
Cited by 81 (27 self)
- Add to MetaCart
All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation
An Autonomous Spacecraft Agent Prototype
- Autonomous Robots
, 1997
"... This paper describes the New Millennium Remote Agent #NMRA# architecture for autonomous spacecraft control systems. This architecture integrates traditional real-time monitoring and control with constraintbased planning and scheduling, robust multi-threaded execution, and model-based diagnosis ..."
Abstract
-
Cited by 74 (22 self)
- Add to MetaCart
(Show Context)
This paper describes the New Millennium Remote Agent #NMRA# architecture for autonomous spacecraft control systems. This architecture integrates traditional real-time monitoring and control with constraintbased planning and scheduling, robust multi-threaded execution, and model-based diagnosis and recon#guration.
Reformulating Temporal Plans For Efficient Execution
- In Principles of Knowledge Representation and Reasoning
, 1998
"... The Simple Temporal Network formalism permits significant flexibility in specifying the occurrence time of events in temporal plans. However, to retain this flexibility during execution, there is a need to propagate the actual execution times of past events so that the occurrence windows of future e ..."
Abstract
-
Cited by 72 (11 self)
- Add to MetaCart
(Show Context)
The Simple Temporal Network formalism permits significant flexibility in specifying the occurrence time of events in temporal plans. However, to retain this flexibility during execution, there is a need to propagate the actual execution times of past events so that the occurrence windows of future events are adjusted appropriately. Unfortunately, this may run afoul of tight real-time control requirements that dictate extreme efficiency. The performance may be improved by restricting the propagation. However, a fast, locally propagating, execution controller may incorrectly execute a consistent plan. To resolve this dilemma, we identify a class of dispatchable networks that are guaranteed to execute correctly under local propagation. We show that every consistent temporal plan can be reformulated as an equivalent dispatchable network, and we present an algorithm that constructs such a network. Moreover, the constructed network is shown to have a minimum number of edges among all such n...
CPEF: A continuous planning and execution framework
- AI Magazine
, 1999
"... s This article reports on the first phase of the continuous planning and execution framework (CPEF), a system that employs sophisticated plan-generation, -execution, -monitoring, and -repair capabilities to solve complex tasks in unpredictable and dynamic environments. CPEF embraces the philosophy ..."
Abstract
-
Cited by 70 (3 self)
- Add to MetaCart
(Show Context)
s This article reports on the first phase of the continuous planning and execution framework (CPEF), a system that employs sophisticated plan-generation, -execution, -monitoring, and -repair capabilities to solve complex tasks in unpredictable and dynamic environments. CPEF embraces the philosophy that plans are dynamic, open-ended artifacts that must evolve in response to an ever-changing environment. In particular, plans and activities are updated in response to new information and requirements to ensure that they remain viable and relevant. Users are an integral part of the process, providing input that influences plan generation, repair, and overall system control. CPEF has been applied successfully to generate, execute, and repair complex plans for gaining and maintaining air superiority within a simulated operating environment. T he AI planning community, until recently, has focused its attention almost exclusively on the problem of generation: producing a schedule of activities that when performed in some initial state will guarantee achievement of a specified set of goals. With the exception of plan repair, important topics related to the use of plans (robust execution, reactivity, monitoring, evaluation) have received significantly less consideration. In realistic domains, however, plan generation is only a small component of the overall package. This article reports on the first phase of an effort to develop a system, the continuous planning and execution framework (CPEF), that combines sophisticated plan-generation and planuse capabilities to solve complex tasks in unpredictable and dynamic environments. CPEF embraces the philosophy that plans are dynamic, open-ended artifacts that must evolve in response to an ever-changing environment. In particular, plans must be updated in response to new information and requirements in a timely fashion to ensure that they remain viable and relevant. Plan execution involves more than blind adherence to previously generated plans. Rather, run-time decisions are made to adapt, initiate, or abandon plans and activities in response to current considerations within the operating environment. To date, the emphasis for CPEF has been to produce a distributed, multiagent framework in which plan generation and execution are fluidly integrated. The system provides timely adaptation of its activities based on monitoring of critical events within its operating environment. Users are an integral part of the overall process, providing input that will influence the types of plan that are generated, the number of options to consider, failure assessments, plan-repair strategies, and overall control of system behavior. One unique characteristic of CPEF is that it supports both direct execution, in which activities and actions are undertaken by the system itself, and indirect execution, in which the system supervises execution of plans by a collection of distributed execution entities. The indirect model of execution is essential for many domains, including work-flow management and many classes of military operations, where software control of plan entities is impossible. CPEF leverages several sophisticated AI technologies as components. SIPE-2 (Wilkins 1988) provides hierarchical task network (HTN) planning and plan-repair capabilities. The ADVISABLE PLANNER
A common knowledge representation for plan generation and reactive execution.
- Journal of Logic and Computation,
, 1995
"... ..."
(Show Context)
Interactive Conceptual Tutoring in Atlas-Andes
- In
, 2001
"... The goal of the Atlas project is to increase the opportunities for students to construct their own knowledge by conversing (in typed form) with a natural language-based ITS. Our previous research (Freedman et al., 2000; Freedman, 2000; Ros'e, 2000) has produced reusable components and tools f ..."
Abstract
-
Cited by 61 (32 self)
- Add to MetaCart
The goal of the Atlas project is to increase the opportunities for students to construct their own knowledge by conversing (in typed form) with a natural language-based ITS. Our previous research (Freedman et al., 2000; Freedman, 2000; Ros'e, 2000) has produced reusable components and tools for facilitating the development of domain specific tutorial dialogue systems. The domain independent Atlas system (Freedman et al., 2000) provides a general purpose planning engine and robust input understanding component that can be used to augment any tutoring system with dialogue capabilities. Natural language dialogue, which involves language understanding, planning, and language generation, offers a number of attractive features for intelligent tutoring systems. First, providing the opportunity for natural language input allows the system to assess student understanding based on the direct evidence of the content of student explanations rather than based on the indirect evidence of the problem solving mistakes the students make. Natural language dialogue provides a context in which the system can tailor its presentation of material more directly to the students' needs, for example by addressing student misconceptions immediately as they arise in conversation. Secondly, it gives students the opportunity to gain experience using the language of the domain they are learning. In contrast to using short menu interfaces, requiring students to type an answer triggers recall memory as opposed to recognition memory. Natural language dialogue makes it possible to build a more sophisticated type of tutor. In addition to the hints that many current tutors give, we can extend the tutor's repertoire to include the types of remediation subdialogues seen in natural human tutor...
A procedural knowledge approach to task-level control
- In Proceedings of the Third International Conference on AI Planning Systems
, 1996
"... Effective task-level control is critical for robots that are to engage in purposeful activity in real-world environments. This paper describes PRS-Lite, a task-level controller grounded in a proce-dural knowledge approach to action description. The controUer embodies much of the philosophy that unde ..."
Abstract
-
Cited by 53 (4 self)
- Add to MetaCart
(Show Context)
Effective task-level control is critical for robots that are to engage in purposeful activity in real-world environments. This paper describes PRS-Lite, a task-level controller grounded in a proce-dural knowledge approach to action description. The controUer embodies much of the philosophy that underlies the Procedural Reasoning System (PRS) but in a minimalist fashion. Several fea-tures of PRS-Lite distinguish it from its predeces-sor, including a richer goal semantics and a gener-alized control regime. Both of these features are critical for supporting the management of con-tinuous processes employed in current-generation robots. PRS-Lite has been used extensively as a task-level controller for a robot whose underlying behaviors are implemented as fuzzy rules. Tasks to which it has been applied include vision-based tracking, autonomous exploration, and complex delivery scenaxios.
