L. Gasser and T. Ishida. A Dynamic Organizational Architecture For Adaptive Problem Solving. In Proceedings AAAI-91, pages 185--190, 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....collaboration is an explicit action, and the rules governing such collaborations can be encoded as rules within agent programs. Agent Architectures. For an excellent anthology of classic works on agent systems, see [49] There have been numerous proposals for agentization in the literature (e.g. [35, 43, 17]) which have been broadly classified by Genesereth and Ketchpel [40] into four categories: in the first category, each agent has an associated transducer that converts all incoming messages and requests into a form that is intelligible to the agent. This is clearly not what happens in IMPACT ....

L. Gasser and T. Ishida. A Dynamic Organizational Architecture For Adaptive Problem Solving. In Proceedings AAAI-91, pages 185--190, 1991.

....coordination holds great potential for future developments in the field. Another issue is how to scale up to agent societies of hundreds and thousands of agents. There has been interesting work on cooperative behavior of a large number of agents [22] 27] and on organization self design [13] [18]. However, this work has been done on simple reactive agents operating in artificial environments. Whether or not the results of this work can be applied to more complex agent societies operating in real world environments is an open question. The challenge of how to design large scale agent ....

# L. Gasser and T. Ishida, "A Dynamic Organizational Architecture for Adaptive Problem Solving," Proc. Ninth Nat'l Conf. Artificial Intelligence, pp. 185--190, 1991.

....to each goal held by a respective agent. 4. RELATED WORK Several researchers have addressed the development of adaptive, intelligent, agent based systems. These efforts range from representing coordination and collaboration [1] to production rule based systems for organizational self design [2], to partial global planning [3] to the development of multiagent planning architectures [4] and many others. The majority of previous work has focused on providing architectures with a constrained set of control schemes for agent interaction. In other words, one organization of decision makers ....

....is also an important area of study . Several researchers have investigated how agents can form problem solving groups [17] 1] In addition, centralized, distributed, and group approaches have been compared [18] 19] These studies provide important insight for autonomy reasoning. Gasser and Ishida [2] also provide an understanding of both adaptive self configuration (through Organization SelfDesign) and tradeoffs corresponding to different organizational structures. 5. RESEARCH APPROACH The Sensible Agent architecture (Figure 1) permits dynamic adaptation of agent autonomy. One agent is ....

Gasser, L., and Ishida, T. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185-190. American Association for Artificial Intelligence 1991.

.... self configuration allows agents to reason about and change the organization of their coordination frameworks (Gasser, 1988) Most self organizing systems rely on explicit, predefined differences in agent behavior and limit the reorganization primitives to a fixed number of predefined behaviors (Gasser and Ishida, 1991; Glance and Huberman, 1993; Ishida et al. 1992) Others are based on adapting applicationspecific roles that agents can play during problem solving (Glaser and Morignot, 1997) These systems do not explicitly represent the agent s problem solving role. This limits the ability of these systems ....

Gasser, L. and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. Proceedings of the Ninth National Conference on Artificial Intelligence, 185-190.

....to coordination holds great potential for future developments in the field. Another issue is how to scale up to agent societies of hundreds and thousands of agents. There has been interesting work on cooperative behavior of a large number of agents [22, 27] and on organization self design [13, 18]. However, this work has been done on simple reactive agents operating in artificial environments. Whether or not the results of this work can be applied to more complex agent societies operating in real world environments is an open question. The challenge of how to design large scale agent ....

L. Gasser and T. Ishida, "A Dynamic Organizational Architecture for Adaptive Problem Solving," Proc. Ninth Nat'l Conf. Artificial Intelligence, 1991, pp. 185--190.

.... of their coordination frameworks (Gasser, 1988) Several researchers have made progress toward this objective; however, many of these self organizing systems rely on explicit, predefined differences in agent behavior and limit the reorganization primitives to a fixed number of predefined behaviors (Gasser and Ishida, 1991; Glance and Huberman, 1993; Ishida et al. 1992) Others are based on dynamic participation in application specific roles that agents can play during problem solving (Glaser and Morignot, 1997; Sycara and Pannu, 1998; Tambe, 1997) Some specific research that has contributed to flexible, adaptive ....

.... roles that agents can play during problem solving (Glaser and Morignot, 1997; Sycara and Pannu, 1998; Tambe, 1997) Some specific research that has contributed to flexible, adaptive multi agent coordination includes partial global planning (Durfee and Lesser, 1987) organizational selfdesign (Gasser and Ishida, 1991; Ishida et al. 1992) STEAM flexible teamwork (Kaminka and Tambe, 1998; Tambe, 1997) RETSINA matchmaking (Sycara and Pannu, 1998) and organizational fluidity (Glance and Huberman, 1993) Sensible Agents Sensible Agents are agents whose behavior is based on an understanding of the tradeoffs ....

Gasser, L. and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185-190: American Association for Artificial Intelligence.

....PGP research assumes a statically defined meta level organization, defined during system creation. Thus the ability to dynamically modify agent interactions is not supported. Organizational self design (OSD) provides one strategy for adaptive strategic work allocation and load balancing (Gasser and Ishida, 1991; Ishida et al. 1992) The reorganization primitives provided by OSD dynamically vary the system macro architecture, while the micro architecture (the structure of agents themselves) remains the same. Dynamic reorganization is supported by two primitives: decomposition and composition. ....

....agent s position in the organizational structure of the system is not specified explicitly nor in a domain independent fashion. Most self organizing systems rely on explicit, predefined differences in agent behavior and limit the reorganization primitives to a fixed number of predefined behaviors (Gasser and Ishida, 1991; Glance and Huberman, 1993; Ishida et al. 1992) Others are based on adapting application specific roles that agents can play during problem solving (Glaser and Morignot, 1997) These systems do not explicitly represent the agent s problem solving role. This limits the ability of these systems ....

Gasser, L. and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185-190. American Assosciation for Artificial Intelligence.

....of dynamic creation and destruction of agents [Ishida, Gasser, Yokoo 1992] The mechanics of changing organizational structure is also an important area of study. Several researchers have investigated how agents can form problem solving groups [Numaoka 1992, Jennings Mamdani 1992] Gasser and Ishida [1991] provide an understanding of both adaptive self configuration (through Organization Self Design) and tradeoffs corresponding to different organizational structures. Approach Figure 3 depicts an agent architecture, which supports dynamic adaptive autonomy. Each agent consists of five major ....

Gasser, L., and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185190. American Association for Artificial Intelligence.

.... selfconfiguration: allowing agents to reason about and change the organization of their coordination frameworks (Gasser, 1988) Most self organizing systems rely on explicit, predefined differences in agent behavior and limit the reorganization primitives to a fixed number of predefined behaviors (Gasser and Ishida, 1991; Glance and Huberman, 1993; Ishida et al. 1992) Others are based on adapting application specific roles that agents can play during problem solving (Glaser and Morignot, 1997) These systems do not explicitly represent the agent s problem solving role. This limits the ability of these systems ....

Gasser, L. and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185-190. American Assosciation for Artificial Intelligence.

....collaboration is an explicit action, and the rules governing such collaborations can be encoded as rules within agent programs. Agent Architectures. For an excellent anthology of classic works on agent systems, see [49] There have been numerous proposals for agentization in the literature (e.g. [35, 43, 17]) which have been broadly classified by Genesereth and Ketchpel [40] into four categories: in the first category, each agent has an associated transducer that converts all incoming messages and requests into a form that is intelligible to the agent. This is clearly not what happens in IMPACT ....

L. Gasser and T. Ishida. A Dynamic Organizational Architecture For Adaptive Problem Solving. In Proceedings AAAI-91, pages 185--190, 1991.

....collaboration is an explicit action, and the rules governing such collaborations can be encoded as rules within agent programs. Agent Architectures. For an excellent anthology of classic works on agent systems, see [57] There have been numerous proposals for agentization in the literature (e.g. [38, 46, 16]) which have been broadly classified by Genesereth and Ketchpel [43] into four categories: in the first category, each agent has an associated transducer that converts all incoming messages and requests into a form that is intelligible to the agent. This is clearly not what happens in IMPACT ....

L. Gasser and T. Ishida. A Dynamic Organizational Architecture For Adaptive Problem Solving. In: Proc. AAAI '91, pp 185--190, 1991.

.... of agents are to perform a distributed search task, the organizational structure specifies the decomposition of the search space among the agents and the way the overall search should be coordinated among the agents in terms of which agent should communicate what information to which agent when [ Lesser, 1991 ] a) b) l = 0 l = 1 l = 2 l = 0 d d d d d d d d d d d d d d d d d d d d l = 1 Figure 1: a) 2 level binary tree. b) one level 4 ary tree An analogy with a single agent search process can be made for the distributed search case. The so called weak methods of search can be seen as a set of ....

Les Gasser and Toru Ishida. A dynamic organizational architecture for adaptive problem solving. In Proceedings of the National Conference on Artificial Intelligence, pages 185--190, July 1991.

.... to subscribe to particular agent architectures (which one would assume will be adapted to the task environment at hand) and I may ask questions about the inherent social nature of the task environment at hand (allowing that the concept of society may arise before the concept of individual agents [Gasser, 1991]) Such a conception is unique among computational approaches. I will adapt Shoham s Agent Oriented Programming terminology when I need to be more specific about an agent s internal architecture (in Chapter 5) ffl The representation of the task structure from three different viewpoints. The ....

....of knowledge, resources, and actions out of which agents actively and flexibly construct and reconstruct themselves by adding and subtracting resources and changing agent knowledge boundaries. It is the overall collection of problem solving knowledge that is fixed not the definition of agents. [Gasser and Ishida, 1991] This provides a potentially more open system and social perspective than is usual in DAI research [Hewitt, 1991, Gasser, 1991] A final problem remains with the form of the model that I can only address as a future direction : that of the mutual construction of agents and their environment. ....

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Les Gasser and Toru Ishida. A dynamic organizational architecture for adaptive problem solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, pages 185--190, Anaheim, July 1991.

....there are not enough of them to saturate the bottleneck, and other agents no longer use the resource at all. The uncertainty is still there, but it no longer has an impact on the agents decision making process. A similar example is Gasser and Ishida s work on self organizing production systems [Gasser and Ishida, 1991] where dynamic changes in the environment allowed the system to reorganize itself for more efficient performance. We could potentially analyze either of these systems. ....

Gasser, Les and Ishida, Toru 1991. A dynamic organizational architecture for adaptive problem solving. In Proceedings of the NinthNational Conference on Artificial Intelligence, Anaheim. 185--190.

....to face important issues, related also to decision theory, such as the (dynamic) partitioning over time of the available computational resources between the metacontrol (metaplanning) and the agent society activities. While some examples of reorganization are reported in the DAI literature (e.g. [14]) within our framework the emphasis is on knowledge based (meta)control over an agent society in charge of controlling a robot. Inside the multiagent framework and by means of the software environment described hereafter, we can now investigate, at least experimentally, selection and adaptation ....

Gasser L., Ishida T.: "A Dynamic Organizational Architecture for Adaptive Problem Solving", Proceedings of AAAI Conference, June 1991,

....of dynamic creation and destruction of agents [Ishida, Gasser, Yokoo 1992] The mechanics of changing organizational structure is also an important area of study. Several researchers have investigated how agents can form problem solving groups [Numaoka 1992, Jennings Mamdani 1992] Gasser and Ishida [1991] provide an understanding of both adaptive self configuration (through Organization Self Design) and tradeoffs corresponding to different organizational structures. Approach Figure 3 depicts an agent architecture, which supports dynamic adaptive autonomy. Each agent consists of five major ....

Gasser, L., and Ishida, T. 1991. A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of the Ninth National Conference on Artificial Intelligence, 185190.

....developed programs available on the Web, and this number is increasing on a regular basis. However, we do not address issues such as load balancing and privacy issues addressed by Decker et al. 3] With respect to agent architectures, there have been numerous proposals in the literature (e.g. [4, 6, 1]) which have been broadly classified by Genesereth and Ketchpel[5] into four categories: in the first category, each agent has an associated transducer that converts all incoming messages and requests into a form that is intelligible to the agent. This is clearly not what happens in IMPACT ....

L. Gasser and T. Ishida. (1991) A Dynamic Organizational Architecture For Adaptive Problem Solving, Proc. of AAAI-91, California, pps 185--190.

....skills that a person might acquire in kindergarten, and highlighting important unresolved problems facing the field. Introduction In the pursuit of artificial intelligence (AI) it has become increasingly clear that intelligence, whatever it is, has a strong social component [ Bobrow, 1991; Gasser, 1991 ] Tests for intelligence, such as the Turing test, generally rely on having an (assumedly) intelligent agent evaluate the agent in question by interacting with it. For an agent to be intelligent under such criteria, therefore, it has to be able to participate in a society of agents. Distributed ....

....and evolving, while acknowledged in early DAI work, has only recently been given due attention. Based on sociological ideas, Gasser s work has emphasized the dynamics of organizations [ Gasser et al. 1989 ] and in joint work with Ishida has explored techniques for organizational self design [ Gasser and Ishida, 1991 ] Research on computational ecologies [ Hogg and Huberman, 1991; Kephart et al. 1989 ] has similarly been concerned with how agent populations will evolve to meet the needs of a changing environment. Eventually, Everything Dies This is my paraphrase for one of Fulghum s points. From a DAI ....

[Article contains additional citation context not shown here]

Gasser, Les and Ishida, Toru 1991. A dynamic organizational architecture for adaptive problem solving. In Proceedings of the Ninth National Conference on Artificial Intelligence. 185--190.

....1985; Ishida, 1991] where rules are fired in parallel to reduce the total number of sequential production cycles, while rule firings are globally synchronized in each production cycle. 2. Asynchronous parallel production systems or distributedproduction systems [Ishida et al. 1990; 1992; Gasser and Ishida, 1991] where rules are distributed among multiple processes, and fired in parallel without global synchronization. 3. Multiagent production systems [Ishida, 1992b] where multiple production system programs compete or cooperate to solve a single problem or multiple problems. Since production systems ....

L. Gasser and T. Ishida, "A Dynamic Organizational Architecture for Adaptive Problem Solving," AAAI-91,pp.185-190, 1991.

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Gasser, L. and Ishida, T.: A Dynamic Organizational Architecture for Adaptive Problem Solving. In Proceedings of Ninth National Conference on Artificial Intelligence, (Anaheim, CA, 1991) 185-190.

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