All Outputs (6)

CBR driven interactive explainable AI. (2023)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., MARTIN, K., CORSAR, D., NKISI-ORJI, I., PALIHAWADANA, C., BRIDGE, D., PRADEEP, P., AGUDO, B.D. and CARO-MARTÍNEZ, M. 2023. CBR driven interactive explainable AI. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages169-184. Available from: https://doi.org/10.1007/978-3-031-40177-0_11

Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Numerous explanation techniques (explainers) exist in the literature, and recent findings suggest that addressing multiple user needs requi... Read More about CBR driven interactive explainable AI..

Failure-driven transformational case reuse of explanation strategies in CloodCBR. (2023)
Conference Proceeding
NKISI-ORJI, I., PALIHAWADANA, C., WIRATUNGA, N., WIJEKOON, A. and CORSAR, D. 2023. Failure-driven transformational case reuse of explanation strategies in CloodCBR. In Massie, S. and Chakraborti, S. (eds.) Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023 (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages 279-293. Available from: https://doi.org/10.1007/978-3-031-40177-0_18

In this paper, we propose a novel approach to improve problem-solving efficiency through the reuse of case solutions. Specifically, we introduce the concept of failure-driven transformational case reuse of explanation strategies, which involves trans... Read More about Failure-driven transformational case reuse of explanation strategies in CloodCBR..

iSee: intelligent sharing of explanation experiences. (2023)
Conference Proceeding
MARTIN, K., WIJEKOON, A., WIRATUNGA, N., PALIHAWADANA, C., NKISI-ORJI, I., CORSAR, D., DÍAZ-AGUDO, B., RECIO-GARCÍA, J.A., CARO-MARTÍNEZ, M., BRIDGE, D., PRADEEP, P., LIRET, A. and FLEISCH, B. 2022. iSee: intelligent sharing of explanation experiences. In Reuss, P. and Schönborn, J. (eds.) Workshop proceedings of the 30th International conference on case-based reasoning (ICCBR-WS 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3389. Aachen: CEUR-WS [online], pages 231-232. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_Workshop_paper_83.pdf

The right to an explanation of the decision reached by a machine learning (ML) model is now an EU regulation. However, different system stakeholders may have different background knowledge, competencies and goals, thus requiring different kinds of ex... Read More about iSee: intelligent sharing of explanation experiences..

Introducing Clood CBR: a cloud based CBR framework. (2023)
Conference Proceeding
PALIHAWADANA, C., NKISI-ORJI, I., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2022. Introducing Clood CBR: a cloud based CBR framework. In Reuss, P. and Schönborn, J. (eds.) Workshop proceedings of the 30th International conference on case-based reasoning (ICCBR-WS 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3389. Aachen: CEUR-WS [online], pages 233-234. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_Workshop_paper_108.pdf

CBR applications have been deployed in a wide range of sectors, from pharmaceuticals; to defence and aerospace to IoT and transportation, to poetry and music generation; for example. However, a majority of applications have been built using monolithi... Read More about Introducing Clood CBR: a cloud based CBR framework..

Explainable weather forecasts through an LSTM-CBR twin system. (2023)
Conference Proceeding
PIRIE, C., SURESH, M., SALIMI, P., PALIHAWADANA, C. and NANAYAKKARA, G. 2022. Explainable weather forecasts through an LSTM-CBR twin system. In Reuss, P. and Schönborn, J. (eds.) Workshop proceedings of the 30th International conference on case-based reasoning (ICCBR-WS 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3389. Aachen: CEUR-WS [online], pages 256-260. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_XCBR_Challenge_RGU.pdf

In this paper, we explore two methods for explaining LSTM-based temperature forecasts using previous 14 day progressions of humidity and pressure. First, we propose and evaluate an LSTM-CBR twin system that generates nearest-neighbors that can be vis... Read More about Explainable weather forecasts through an LSTM-CBR twin system..

iSee: intelligent sharing of explanation experience of users for users. (2023)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., PALIHAWADANA, C., NKISI-ORJI, I., CORSAR, D. and MARTIN, K. 2023. iSee: intelligent sharing of explanation experience of users for users. In IUI '23 companion: companion proceedings of the 28th Intelligent user interfaces international conference 2023 (IUI 2023), 27-31 March 2023, Sydney, Australia. New York: ACM [online], pages 79-82. Available from: https://doi.org/10.1145/3581754.3584137

The right to obtain an explanation of the decision reached by an Artificial Intelligence (AI) model is now an EU regulation. Different stakeholders of an AI system (e.g. managers, developers, auditors, etc.) may have different background knowledge, c... Read More about iSee: intelligent sharing of explanation experience of users for users..