Kristian J. Hammond. Planning and Goal Interaction: The Use of Past Solutions in Present Situations. In Proceedings of the Third National Conference on Artificial Intelligence, pages 148--151, Washington D.C., U.S.A., August 22 -- 26 1983. American Association for Artificial Intelligence.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....extension of Sussman s ideas of retrieval and repair and an application of case based reasoning to planning. This approach is also characterized as memory based because the organization of the memory of previous plans is changed during the planning process. CHEF [Ham86a, Ham86b, Ham89] and WOK [Ham83]) is a case based planner that builds new plans out of its memory of old ones. CHEF s domain is Chinese Szechwan cooking and its task is to build new recipes on the basis of users requests. CHEF s input is a set of goals for different tastes, textures, ingredients, and type of dishes and its ....

....goal with possible maximum reward. CADDY uses cost as a measurement of plan efficiency, which can be viewed as a negative reward. CADDY tries to find a plan with low estimated costs. 6.2 CADDY and Plan Adaptation We next compare CADDY with several plan adaptation systems. HACKER [Sus75] WOK [Ham83], CHEF [Ham86a, Ham86b, Ham89] PLEXUS [Alt86a, Alt86b, Alt88] GTD paradigm [Sim88a, Sim88b] and CADDY are similar in a number of respects. They are all single agent planning systems; they attempt to use past experiences to overcome current problems encountered; they use a collection of plans to ....

Kristian J. Hammond. Planning and Goal Interaction: The Use of Past Solutions in Present Situations. In Proceedings of the Third National Conference on Artificial Intelligence, pages 148--151, Washington D.C., U.S.A., August 22 -- 26 1983. American Association for Artificial Intelligence.

....technique that uses information from past solutions to guide the problem solver in generating the current solution. CBR has most often been used for inter problem learning where experience in solving other problems is used to help solve a new problem. Examples of systems that use CBR are CHEF [18], KRITIK [17] BOGART [46] and ARGO [24] There are several differences between CBR systems and the systems that use feedback to solve design optimization problems. An obvious one is that CBR has been commonly used for transferring knowledge between problem solving episodes while design ....

....of each clustering is represented by the number on the right of the pairings. The dashed line on the right (the cut line) shows the partitioning of the 16 points into four clusters. The first cluster is at 55 and is composed of the points [55,53,27,23] The other three clusters are: 2) 51 with [51,18,17,40], 3) 50 with [50,48,46,38] and (4) 42 with [42,36,33,21] Cluster 0 left 0 right 3 Cluster 1 left 4 right 7 Cluster 2 left 8 right 11 Cluster 3 left 12 right 15 Figure 4.28: Seed cluster indices find hw cluster( saves the results of partitioning in two arrays. The 16 points are saved in cluster ....

Kristian J. Hammond. Planning and goal interactions: The use of past solutions in present situations. Proceedings of AAAI-83, 1983.

....case in the database consists of a description of the problem and the problem solving steps executed to solve that problem. Much case based research has focussed on the storage and or retrieval of cases (see [1] and the re use of the problem solving steps directly or some perturbation of them [2, 3, 4, 5]. In this paper, we focus on REPLAY 1 , i.e. the technique of replaying as much of the decisions that have been saved in a decision tree as is applicable. This technique is central to case based reasoning because how the prototypes are used determines the amount and type of information that ....

....are used determines the amount and type of information that should be saved with each case. REPLAY techniques form the bulk of the use of case based reasoning either by replaying decisions verbatim, e.g. BOGART [3] and PRIAR [6, 4, 5] and ARGO[7] or by instantiating the prototype, e.g. CHEF [2], KRITIK [8] and BRAINSTORMER [9] A basic premise of REPLAY is that the search for a correct solution is expensive and that it is therefore more efficient to save the decision tree for each case and to replay as many suitable decisions as possible, thereby eliminating the search cost for each of ....

K. J. Hammond, "Planning and goal interactions: The use of past solutions in present situations," Proceedings of AAAI-83, 1983.

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Hammond, K. (1983), Planning and goal interaction: The use of past solutions in present situations.

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