K.S. DeckerandK.Sycara.Intelligent adaptive information agents. Journal Intelligent Information Systems,  Home/Search   Document Details and Download   Summary   Related Articles   Check

....are of interest to him. The system can be viewed as a single agent, and thus the organizational pattern of its elements (in our case, the evolving agents) is not the system s main concern. Other multiagent systems designed for information gathering include the InfoSleuth project [14] Retsina [2, 16], and MACRON [1] 3 2 The similarity between the documents was computed based on the TFIDF formula [15] 3 We mention here only information gathering agent based systems. For a more complete overview of related systems, see [6] 2.2 Domain Considerations for an Organization based Multiagent ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9:239--260, 1997.

....of server B about its own utility, but B can exploit it and bid strategically instead of bidding its true values. The problem considered in this paper is the information problem. How will the server learn about a dataset if it does not store it locally Research on multi agent learning includes [4, 20]. For space reasons, we do not elaborate on the related work here, but in Section 4 we describe relevant work on machine learning that is related to our research. 3. Environment Description We consider an environment in which there is a set of several (more than two) information servers, denoted ....

K. Decker and K. Sycara. Intelligent adaptive information agents. Information Systems, 9:239--260, 1997.

.... agent interaction within a group can be modeled as the fulfillment of certain roles in the domain (e.g. in the football domain there are roles including quarterback, receiver, and blocker) Singh, 1990) Organizational adaptation occurs as agents move in and out of these pre defined roles (Decker and Sycara, 1997; Glaser and Morignot, 1997; Tambe, 1997) When an agent failure is detected, another agent is substituted, if possible, into the failed role. Though the roles that individual agents play within the system s problem solving structure may change, few systems allow agents to change the ....

Decker, K. S. and Sycara, K. P. 1997. Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems 9(3): 239-260.

....uses tf idf filtering to match document characteristics to free text [8] In this paper, we do not address the use of such filtering, because using filtering for matchmaking is orthogonal to our use of ontologies. The larks matchmaking system [19] was developed within the context of the retsina [3] project. retsina matchmakers describe the semantics of their offered services both in terms of signatures (inputs and outputs) but also in terms of the relationships between the inputs and the outputs. They also use tf idf techniques to categorize the semantic relevance of a query to an ....

K. Decker and K.P. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....the demand for robust performance and flexibility increases. Consequently, much research has focused on agent adaptability. Various researchers have identified motivations for agent adaptation including the ability to respond to the failure of another agent or to a communication failure (Decker and Sycara, 1997; Tambe, 1997) to coordinate plans schedules and resolve conflict (Jennings, 1996; Klein, 1991) to balance tasks equally among agents (Fatima and Uma, 1998) to improve system performance (Glance and Huberman, 1995) and to respond to other types of uncertainty present in the environment. Agent ....

.... allowing agents to dynamically 4 assume one or more different pre defined roles during system operation (So and Durfee, 1998) For example, the RETSINA agent approach uses middle agents to help route information requests in the face of the failure and recovery of agents or communication links (Decker and Sycara, 1997). If, for instance, an agent who was fulfilling a particular type of information provider role fails, a middle agent facilitates the placement of another agent in this role. The agents that participate in any particular instance of the organizational structure can be dynamically modified based ....

Decker, K. S. and Sycara, K. P. (1997) Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems 9(3): 239-260.

....interface, internal agentscheduling and monitoring in a fashion similar to operating system primitives. DECAF is the framework used to demonstrate and test the e#ectiveness of the agentscheduling algorithms. DECAF provides the necessary architectural services of a large grained intelligent agent #Decker Sycara 1997; Sycara et al. 1996#: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis #Horling et al. 1999#. Figure 2 represents the high level structure of the DECAF architecture. Structures inside the heavy black line are internal to the ....

Decker, K. S., and Sycara, K. 1997. Intelligent adaptive information agents. Journal of Intelligent Information Systems 9#3#:239#260.

....performance and flexibility has increased. Consequently, much research over the past several years has focused on agent adaptability. Various researchers have identified motivations for agent adaptation including the ability to respond to the failure of another agent or a communication failure [17, 44] , to coordinate plans and resolve conflict [29, 31] to distribute tasks equally among agents [20] to improve system performance [23] and to respond to other types of uncertainty present in the 1 10 100 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Degree of Autonomy Number of ....

.... reconfigured by allowing agents to dynamically assume one or more different pre defined roles during system operation [41] For example, the RETSINA agent approach uses middle agents to help route information requests in the face of the failure and recovery of agents or communication links [17]. If, for instance, an agent who was fulfilling a particular type of information provider role fails, a middle agent facilitates the placement of another agent in this role. The agents that participate in any particular instance of the organizational structure can be dynamically modified based ....

[Article contains additional citation context not shown here]

K. S. Decker and K. P. Sycara, "Intelligent Adaptive Information Agents," Journal of Intelligent Information Systems, vol. 9(3), pp. 239-260, 1997.

.... systems, agent interaction within a group can be modeled as the fulfillment of certain roles in the domain (e.g. in the football domain there are roles including quarterback, receiver, and blocker) Singh, 1990) Organizational adaptation occurs as agents move in and out of these pre defined roles (Decker and Sycara, 1997; Glaser and Morignot, 1997; Tambe, 1997) When an agent failure is detected, another agent is substituted, if possible, into the failed role. Though the roles that individual agents play within the system s problem solving structure may change, few systems allow agents to change the ....

Decker, K. S. and Sycara, K. P. 1997. Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems 9(3): 239-260.

....this world view, agents belong to multiple different organizations, have multiple different roles, have different relationships with different agents, and interact in cooperative and self interested styles. Figure 7 shows a network of organized interacting information agents (in the WARREN style [3]) While a complete description of the network is beyond the scope of this paper, the agents in the network are associated with different corporate entities and interact in a way that reflects their different associations. Additionally, within a given organization, relationships may differ due to ....

K. Decker, M. Williamson, and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9:239--260, 1997.

....need only know the location of the broker and how to query it for information to locate other agents in the system. Each agent then advertises itself to the broker and queries the broker when it needs to locate other agents. A similar brokering system is implemented in the RETSINA architecture [3]. A single broker represents a single point of failure. If the broker cannot be located, no inferencing on the data domain can be performed and everything will stop functioning even though locational information of agents is being cached. A single broker system also represents a hard limit to ....

....similar to InfoSleuth s content based semantic brokering capabilities, but only over information. These systems implicitly do syntactic brokering when matching resources, as they each support a single underlying query language. Systems that go a bit further into semantic brokering include RETSINA [3, 12] and SHADE [6] RETSINA has recently implemented a sophisticated brokering system that includes both syntactic and semantic brokering. The SHADE group focused on semantic matchmaking issues including describing the content of a resource. CORBA [5] is a widely known standard that implements ....

K. Decker and K.P. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3), 1997.

....and monitoring in networks of dynamically appearing and continually changing information sources. Its current Java implementation provides for agent portability across several platforms. We note in passing that there exist many other information centric agent systems. SIMS [AKS96] Warren Retsina [DSW96, DS97], Infomaster [GGKS95] TSIMMIS [GPQR 95] and DISCO [TRV95] all to some MCC Technical Report MCC INSL 096 98 5 degree are information centric agent systems. The designers and implementers of these systems have also addressed some of the issues that we discuss in this paper. A Layered ....

K. Decker and K. Sycara, "Intelligent adaptive information agents". To appear in Journal of Intelligent Information Systems.

....limited in that incorporating new information sources was difficult. Progress in this area was made with the introduction of mediation to facilitate integration, e.g. in [17] Recent researchers have begun addressing the application of agent technology to the problem of heterogeneous data access [7, 13], which further facilitates the integration of data sources. The problem of mapping between representations was irrefutably identified with the development of the ANSI SPARC three schema architecture [2] This framework posed the goal of composing information from heterogeneous sources using a ....

K. Decker and K.P. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

.... agents to mediators to maintain an efficient balance when work loads change (Decker, Sycara, Williamson 1997) Distributed agent system architectures have also been developed to encourage independent agent specialization, so that over time agents can become expert in a particular domain (Decker Sycara 1997; Decker, Sycara, Williamson 1997; Knoblock, Arens, Hsu 1994) These systems allow agents to become knowledge sources, so that agents can build upon the work of other agents. This also creates hierarchies that can form and reform dynamically. Translator complexity The many kinds of ....

Decker, K. S., and Sycara, K. 1997. Intelligent adaptive information agents. Intelligent Information Systems 9:239--260.

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Decker, K. and Sycara, K. "Intelligent Adaptive Information Agents". Journal of Intelligent Information Systems, vol.9, pp. 239-260, 1997.

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K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

.... of the annotation work for each gene can be done independently # biologists wish to both make their findings widely available, yet retain control over the data # new types of analysis and sources of data are appearing constantly We have used DECAF, a multi agent system toolkit based on RETSINA [32, 12, 8]: and TAEMS [11, 34] to construct a prototype multi agent system for automated annotation and database storage of sequencing data for herpesviruses [7] The resulting system eliminates tedious and always out of date hand analyses, makes the data and annotations available for other researchers (or ....

....from the information sources because they are being produced by different organizational entities, usually for different purposes than those of the information gathering user. Examples of information gathering domains are financial information (evaluating, tracking, and managing a stock portfolio)[8, 12], military strategic information (integration of friendly troop movements, enemy observations, weather, satellite data, civilian communications) 19] and annotation of gene sequences (as discussed briefly in the introduction) Solutions to the information gathering problem tend to draw on two ....

[Article contains additional citation context not shown here]

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....of the annotation work for each gene can be done independently; biologists wish to both make their findings widely available, yet retain control over the data; new types of analysis and sources of data are appearing constantly. We have used DECAF, a multi agent system toolkit based on RETSINA [21, 10, 7]: and TAEMS [9, 23] to construct a prototype multi agent system for automated annotation and database storage of sequencing data for herpesviruses [6] The resulting system eliminates tedious and always out of date hand analyses, makes the data and annotations available for other researchers (or ....

....Related Work There has been significant work on general algorithms for query planning, selective materialization, and the optimization of these from the AI perspective, for example TSIMMIS [4] Infosleuth [19] SIMS [1] etc. and of course on applying agents as the way to embody these algorithms [16, 21, 10]. In Biology, compared to the work being done to create the raw data, all the work on how to organize and retrieve it is relatively small. Most of the work in computer science directed to biological data has been in the area of heterogeneous databases, focusing on the semi structured nature of ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....die. Merging of two agents, or self extinction of underutilized agents is an important mechanism to control agent proliferation. Since the agent s own load and the loads of other agents vary over time in a non deterministic way, the decision of whether and when to clone is non trivial. Prior work [4] has presented a model of cloning based on prediction of missed task deadlines and idle times on the agent s schedule in the RETSINA multi agent infrastructure [5] This research implements a stochastic model of decision making based on dynamic programming to determine the optimal timing for ....

K. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9:239-- 260, 1997.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [7, 24]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis. This is essentially the internal operating system of a software agent, to which application programmers have strictly limited access. DECAF provides an environment that allows ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Intelligent Information Systems, 9:239--260, 1997.

....of the annotation work for each gene can be done independently; biologists wish to both make their findings widely available, yet retain control over the data; new types of analysis and sources of data are appearing constantly. We have used DECAF, a multi agent system toolkit based on RETSINA [26, 11, 8]: and TAEMS [10, 28] to construct a prototype multi agent system for automated annotation and database storage of sequencing data for herpesviruses [7] The resulting system eliminates tedious and always out of date hand analyses, makes the data and annotations available for other researchers (or ....

....at many different locations and is constantly being changed or updated, with even new information sources appearing over time. We promote the use of the RETSINA multi agent organization for building information gathering systems. The RETSINA approach consists of three general classes of agents[26, 11]: Information Extraction Agents, which interact directly with external data sources, i.e. wrapping sensors, databases, web pages. Task Agents, which interact only with other agents to handle the bulk of the information processing tasks. These include both domain dependent agents that take ....

[Article contains additional citation context not shown here]

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....software engineering approach to building multiagent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a largegrained intelligent agent [4, 11]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [7] This is essentially the internal operating system of a software agent, to which application programmers have strictly limited access. The control or programming of DECAF ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [5, 14]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [9] This is the internal operating system of a software agent, to which application programmers have strictly limited access. The overall internal architecture of DECAF is ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....internal agent scheduling and monitoring in a fashion similar to operating system primitives. DECAF is the framework used to demonstrate and test the effectiveness of the agent scheduling algorithms. DECAF provides the necessary architectural services of a large grained intelligent agent (Decker Sycara 1997; Sycara et al. 1996) communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis (Horling et al. 1999) Figure 2 represents the high level structure of the DECAF architecture. Structures inside the heavy black line are internal to the ....

Decker, K. S., and Sycara, K. 1997. Intelligent adaptive information agents. Journal of Intelligent Information Systems 9(3):239--260.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [3, 8]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [6] This is essentially the internal operating system of a software agent, to which application programmers have strictly limited access. The control or programming of DECAF ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....pre specified subtask (collection of agent actions) These building blocks are then chained together by the DECAF planner. This paradigm differs from most of the well known agent toolkits, which instead use the API approach to agent construction (e.g. 8] Functionally, DECAF is based on RETSINA [3] and TAEMS[2, 13] Although a traditional HTN planning component is in development, currently the control or programming of DECAF agents is provided via a picture based GUI called the Plan Editor. The Plan Editor can also be used to construct shared task network libraries for common multi agent ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

No context found.

Keith S. Decker and Katia Sycara. 1997. Intelligent adaptive information agents. Intelligent Information Systems, 9:239--260.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent #Decker Sycara 1997; Sycara et al. 1996#: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis #Horling et al. 1999#. This is essentially, the internal #operating system of a software agent, to which application programmers have strictly limited ....

....building blocks are then chained together by the DECAF planner. This paradigm di#ers from most of the well known agent toolkits, which instead use the API approach to agent construction #e.g. #Chauhan 1997; Boloni 1996; Petrie 1996##. Functionally, DECAF is based on RETSINA #Sycara et al. 1996; Decker et al. 1997; Decker Sycara 1997; Williamson, Decker, Sycara 1996b; 1996a# and t#ms #Decker Lesser 1993; Wagner, Garvey, Lesser 1997#. In the absence of a planning component, the control or programming of DECAF agents is provided via a GUI called the Plan Editor. The Plan Editor can also be used to ....

[Article contains additional citation context not shown here]

Decker, K. S., and Sycara, K. 1997. Intelligent adaptive information agents. Intelligent Information Systems 9:239#260.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [5, 16]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [10] This is essentially the internal operating system of a software agent, to which application programmers have strictly limited access. The overall internal architecture of ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Jnl of Intelligent Information Systems, 9(3):239--260, 1997.

....agents. Detecting the existence of such relationships is domain dependent. In a domain such as distributed sensor networks, possible coordination relationships are detected geographically with respect to physical sensor locations[9] In an application such as financial information gathering[11] possible relationships are recorded before a partial plan is distributed to multiple agents. In the hospital scheduling problem, the set of possible relationships are well known medical domain knowledge, and are based on the particular set of tests ordered by the examining doctor and recorded ....

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

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K. Sycara, K. Decker, and M. Williamson. Intelligent adaptive information agents. In Working Notes of the AAAI-96 Workshop on Intelligent Adaptive Agents, Aug 1996.

....agent queries an information agent, which acts as an electronic catalog. In order to run our system using real world data, each of the information agents queries a well known Internet book retailer (Amazon.com, Borders and Barnes Noble) In our system we used Retsina information agents ( [16, 15]) which can be easily adapted to serving data from any website. The information retrieved from the agent is then cached by the supplier agent, which greatly speeds up future access. All bids are submitted to the auctioneer agent ( gure 8) which waits for the auction period to expire and then ....

K. Sycara, K. Decker, and M. Williamson. Intelligent adaptive information agents. In Working Notes of the AAAI-96 Workshop on Intelligent Adaptive Agents, Aug 1996. 20

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K. Sycara, K. Decker, and M. Williamson. Intelligent adaptive information agents. In Working Notes of the AAAI-96 Workshop on Intelligent Adaptive Agents, Aug 1996.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [3, 8]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [7] This is essentially the internal operating system of a software agent, to which application programmers have strictly limited access. The control or programming of DECAF ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [12, 30]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [22] This is essentially, the internal operating system of a software agent, to which application programmers have strictly limited access. The control or programming of DECAF ....

....standard advertisement of such capabilties. Similar to DECAF, JACK will analyze plans and make decisions about sequential or paralle execution, respond apropriately in the event of a failure and decide when sufficient conditions exist to enable an action. Functionally, DECAF is based on RETSINA [30, 9, 12, 34, 33] and TAEMS[11, 31] However, DECAF, has been restructured to provide a platform for rapid development of agents and as a platform for researching specific areas of agent interaction. DECAF is also written in Java 1 , and makes extensive use of the Java threads capabilities to improve ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

No context found.

K. S. Decker and K. Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9#3#:239#260, 1997.

....engineering approach to building multi agent systems. The toolkit provides a stable platform to design, rapidly develop, and execute intelligent agents to achieve solutions in complex software systems. DECAF provides the necessary architectural services of a large grained intelligent agent [6, 20]: communication, planning, scheduling, execution monitoring, coordination, and eventually learning and self diagnosis [14] This is essentially, the internal operating system of a software agent, to which application programmers have strictly limited access. The control or programming of DECAF ....

Keith S. Decker and Katia Sycara. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239--260, 1997.

....a new information agent that is a clone of itself. In this way, the information agent can make a rational metacontrol decision about whether or not it should undertake a cloning behavior. A formal presentation of the cloning criteria and the results of empirical evaluation can be found in [5]. 5 Multi Source Information Agents Basic information agents are certainly useful, but there is a great deal of reusable behavior that is involved with manipulating queries themselves, independent of the ultimate sources of data. We are currently constructing a new class of multi source ....

K. Decker, M. Williamson, and K. Sycara. Intelligent adaptive information agents. In Proceedings of the AAAI-96 Workshop on Intelligent Adaptive Agents, 1996.

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K.S. DeckerandK.Sycara.Intelligent adaptive information agents. Journal Intelligent Information Systems,

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Decker, K.S., and Sycara, K.: Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3) (1997) 239-260.

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Sycara KDK (1997) Intelligent adaptive information agents. J Intell Inf Syst 9(3):239--260

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K. Decker and K. Sycara. Intelligent Adaptive Information Agents. Journal of Intelligent Information Agents, 9:239--260, 1997.

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K. Decker, K.P. Sycara., Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239-260, 1997.

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K. Decker and K. Sycara. Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems, 9:239-260, 1997.

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K. Decker, K.P. Sycara., Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9(3):239-260, 1997.

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Keith Decker, Karia Sycara, and Mike Williamson. Intelligent adaptive information agents. In Ibrahim Imam, editor, Working Notes of the AAAI-96 Workshop on Intelligent Adaptive Agents, Portland, OR, 1996.

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K. S. Decker and K. Sycara, Intelligent Adaptive Information Agents, Journal of Intelligent Information Systems, vol. 9, pp. 239-260, 1997.

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Decker, K. S., and Sycara, K. Intelligent adaptive information agents. Journal of Intelligent Information Systems, 9 #1997#, 239#260.

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K. Decker, K. Sycara. Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems, 9, pp. 239-260, 1997

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K. Decker, K. Sycara. Intelligent Adaptive Information Agents. Journal of Intelligent Information Systems, 9, pp. 239-260, 1997

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K. Decker and K.P. Sycara. Intelligent adaptive information agents. Journal of Intelligent Infromation Systems, 9(3):239--260, 1997.

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