Andrea Bonzano's research while affiliated with Trinity College Dublin and other places
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Publications (12)
We can learn a lot about what features are important for retrieval by comparing similar cases in a case-base. We can determine which features are important in predicting outcomes and we can assign weights to features accordingly. In the same manner we can discover which features are important in specific contexts and determine localised feature wei...
Case-Based Reasoning (CBR) has emerged from research in cognitive psychology as a model of human memory and remembering. It has been embraced by researchers of AI applications as a methodology that avoids some of the knowledge acquisition and reasoning problems that occur with other methods for developing knowledge-based systems. In this paper we p...
Case-Based Reasoning (CBR) has emerged from research in cognitive psychology as a model of human memory and remembering. It has been embraced by researchers of AI applications as a methodology that avoids some of the knowledge acquisition and reasoning problems that occur with other methods for developing knowledge-based systems. In this paper we p...
One problem with using CBR for diagnosis is that a full case description may not be available at the beginning of the diagnosis. The standard CBR methodology requires a detailed case description in order to perform case retrieval and this is often not practical in diagnosis. We describe two fault diagnosis tasks where many features may make up a ca...
In this paper we present a Case-Based Reasoning system that helps air traffic controllers to solve aircraft conflicts. In particular, we focus on the hierarchical aspect of the CBR system which is able to solve multiple aircraft conflicts, i.e. conflicts that involve three or more aircraft. It is not practical to build a case-base for the different...
ratitude to the controllers of the Eurocontrol Experimental Centre: Andrew Barff, Peter Csarnoy, Ray Dowdall, Frank Dowling, Peter Eriksen, Robin Hill, Diarmuid Houlihan, Paul Humphreys, Roger Lane, Leif Lundquist, Rod McGregor, Hugh O'Connors, John O'Gorman (Dublin Airport), Guy Tod, Nigel S. Thorne, Michael Weldon (Irish Aviation Authority), Paul...
k-Nearest Neighbour is a popular case retrieval technique in Case-Based Reasoning. It has the disadvantage that its accuracy depends strongly on the weights assigned to the case features. This problem can be addressed by using Introspective Learning to discover appropriate values for feature weights. The basic idea with Introspective Learning (IL)...
We can learn a lot about what features are importan t for retrieval by comparing similar cases in a case-base. We can dete rmine which features are important in predicting outcomes and we can ass ign weights to features accordingly. In the same manner we can discover whi ch features are important in specific contexts and determine locali sed featur...
. The conflict resolution task performed by air-traffic controllers appears a suitable task for automation using CBR. This is because human competence seems to involve recognising situations and reusing solutions. In this paper we present our experiences in developing a CBR system to support this conflict resolution task. We discuss the problems of...
One problem with using CBR for diagnosis is that for many diagnosis tasks a full case description may not be available at the beginning of the diagnosis. The standard CBR methodology requires a detailed case description in order to perform case retrieval and this may not be practical in medical or technical diagnosis. In this paper we describe medi...
Citations
... We note that the incremental nature of our algorithm is analogous to Broder (1990)'s incremental nearest neighbor search which also finds kNN iteratively starting from the first, ending with the k th ; but it differs from the incremental retrieval concept of Cunningham, Smyth, and Bonzano (1998) and Jurisica, Glasgow, and Mylopoulos (2000) because there, the iteration takes place in conversational CBR systems where the retrieval is incrementally refined via iterative user interactions. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272338407129166-1441941945035_Q64/Padraig-Cunningham.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272447295455245-1441967905523_Q64/Barry-Smyth.jpg)
... The presence of C reset indicates a potential defect in the similarity measure. One strategy for addressing similarity defects, pursued in this paper and elsewhere [3], is to adjust feature weights. Other issues such as insufficient vocabulary knowledge and noisy cases might also lead to resets, but are beyond the scope of this paper. ...
... The weighted nearest neighbour method (wNN) is a popular similarity measure commonly used in case-based reasoning (CBR) systems [1]. The accuracy of the wNN algorithm depends highly on finding appropriate attribute weights [2]. Most inference engines use global weights, i.e. the weight of an attribute remains constant over the run of the algorithm or over the domain [3]. ...
... Complex, high density airspace Bonzano and Cunningham (1998) ...
... knowledge base and avoids repeating the same mistakes. In the ATC domain, Bonzano et al. (1996) and Liang (2015) showed that a Case-Based Reasoning (CBR) approach can be used in DSS during conflict resolution tasks. The principle of CBR is to solve a new situation by reusing the solution of the most similar previous case. ...
... In the developed application the knowledge about past projects is foreseen to be simply stored in the databases. In a casebased reasoning system usually the knowledge is indexed so that similarity metric allow to retrieve in the database existing knowledge relevant to the design [119,120]. Include the electrical and automation part of the design of a manufacturing systems. In the era of the Industry 4.0 concept a great part of the design of a production line is taken by electrical and automation engineering. ...
... Craw et al. [11] developed a method to optimize CBR retrieval. Bonzano et al. [8] combines introspective learning for feature weighting in CBR. Feature weights for a set of cases are adjusted dynamically during case retrieval by Zhang and Yang [57]. ...
... The incremental approach kind of matches the users statement to correct attribute-value pairs. A similar approach is presented by Cunningham et al. in [26,27] . They introduce the Incremental CBR (I-CBR) mechanism for diagnosis. ...
... Evaluation of the new cases is carried out and solutions suggested in the revise phase and the new cases are then added to the case repository for future learning, as a part of the retain phase [64]. One of the examples of CBR application is Intelligent Systems for Aircraft Conflict Resolution (ISAC) [65] which was developed to help the decision-making process of aircraft controllers to resolve the conflicts between aircraft. CBR is one of the most commonly used reasoning systems, as its architecture has the capability of accommodating any advanced algorithms, mainly text processing techniques. ...
... There have been various attempts to explicitly model the controller's conflict resolution strategies, 31,35,79,131,132 although efforts to embed these in automation have proven difficult. 19,133 One such effort is EUROCONTROL's CORA, which aimed to create a conflict resolution decision aid around a core of controller heuristic solutions. ...
