Research Impact

ABA⁺

I advanced the main contributions of my PhD in the paper ABA⁺: Assumption-Based Argumentation with Preferences, published at KR 2016. ABA⁺ extends the well established structured argumentation formalism ABA with preferences. This research has since continued by efforts of mine as well as researchers internationally.

I have proposed and overseen an undergraduate student research project to co-develop the system ABAplus implementing ABA⁺, also resulting into a paper at PRIMA 2017.
In collaboration with health informaticians from Imperial and King's, I wrote the early paper Argumentation for Explainable Reasoning with Conflicting Medical Recommendations describing in part the ABA⁺-based component of the decision support system to be developed as part of the ROAD2H project.
Collaborating internationally with Tiago Oliveira, I developed the ABA⁺G formalism, presented at KR 2018 and AAMAS 2019.
I am managing and working with Amin Karamlou, a promising early researcher, on extending, implementing and applying ABA⁺G to medical reasoning.
I have taught ABA⁺, as well as more generally argumentation with preferences, as part of a Master's level course at Imperial.
Material on preferences has also appeared in the chapter on ABA in Handbook Of Formal Argumentation (2018).
I have presented ABA⁺ to various audiences, at places such as King's College London and Luxembourg University.
ABA⁺ is being further studied by my international colleagues, for instance as regards its semantics and preference handling, with complexity results published at AAAI 2019.

AA-CBR

As part of my PhD studies, I did an overseas research internship with Prof Ken Satoh at NII, Tokyo, on applying argumentation to legal reasoning, which resulted into the AA-CBR formalism, published at KR 2016. AA-CBR is a machine learning (case-based reasoning)-inspired and abstract argumentation-driven methodology for explainable prediction (classification).

We first advanced AA-CBR explanations in COMMA 2016 paper.
We later proposed, with a (then) PhD student, integrating ANNs with AA-CBR for explanatory predictions in XAI 2018 paper.
In a very successful interdisciplinary collaboration with Thomson Reuters, I advanced a methodology and developed a system for explaining UK primary legislation outcomes, published in 2019 in the leading journal on applications of expert systems, ESWA.
AA-CBR has been taught as part of a Master's level course at Imperial.
Study of AA-CBR has been further taken up by students under my supervision, as well as PhD students at Imperial.
AA-CBR has reached various audiences, at places such as Tokyo and Swansea.
AA-CBR has been generalised to provide dialectically explainable predictions for categorical data, image classification and text sentiment analysis.

Explainable AI

The above research on ABA⁺ and AA-CBR falls into the overarching theme of XAI under which I undertook other research activities.

Explainable Scheduling

Developed methodology for explaining makespan scheduling using abstract argumentation.
Supervised a Master's student in implementing a research tool supporting explainable scheduling.
Oversaw development of a web app to interface with the AI-assisted Schedule Explainer.
Published AI-assisted Schedule Explainer for nurse rostering as a demo at AAMAS 2020.
Engaged with general public and presented Schedule Explainer to a numerous audience during The Great Exhibition Road Festival.
Participated in British Computer Society (BCS) Specialist Group on AI (SGAI) Machine Intelligence Competition with Schedule Explainer.

List of Publications

Journal, Conference and Workshop Papers, Book Chapters

K. Čyras, A. Karamlou, M. Lee, D. Letsios, R. Misener, F. Toni: AI-assisted Schedule Explainer for Nurse Rostering
International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020)
O. Cocarascu, A. Stylianou, K. Čyras, F. Toni: Data-Empowered Argumentation for Dialectically Explainable Predictions
European Conference on Artificial Intelligence (ECAI 2020)
K. Čyras, T. Oliveira: Resolving Conflicts in Clinical Guidelines using Argumentation
International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019)
A. Karamlou, K. Čyras, F. Toni: Complexity Results and Algorithms for Bipolar Argumentation
International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019)
A. Karamlou, K. Čyras, F. Toni: Deciding the Winner of a Debate Using Bipolar Argumentation
International Conference on Autonomous Agents and Multiagent Systems (Demo Session) (AAMAS 2019)
K. Čyras, D. Birch, Y. Guo, F. Toni, R. Dulay, S. Turvey, D. Greenberg, T. Hapuarachchi: Explanations by Arbitrated Argumentative Dispute
Expert Systems with Applications (ESWA), 2019
K. Čyras, D. Letsios, R. Misener, F. Toni: Argumentation for Explainable Scheduling
The 33^rd AAAI Conference on Artificial Intelligence (AAAI 2019)
K. Čyras, T. Oliveira: Argumentation for Reasoning with Conflicting Clinical Guidelines and Preferences
The 16^th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018)
K. Čyras, B. Delaney, D. Prociuk, F. Toni, M. Chapman, J. Dominguez, V. Curcin: Argumentation for Explainable Reasoning with Conflicting Medical Recommendations
Reasoning with Ambiguous and Conflicting Evidence and Recommendations in Medicine (MedRACER 2018, KR 2018 Workshop)
K. Čyras, T. Oliveira, M. Williams, L. Bozzato, M. Homola, T. Mossakowski, A. Zimmermann: Proceedings of the Joint Proceedings of Reasoning with Ambiguous and Conflicting Evidence and Recommendations in Medicine (MedRACER 2018) and the 3^rd International Workshop on Ontology Modularity, Contextuality, and Evolution (WOMoCoE 2018) co-located with the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018)
O. Cocarascu, K. Čyras, F. Toni: Explanatory Predictions with Artificial Neural Networks and Argumentation
IJCAI-ECAI 2018 Workshop on Explainable Artificial Intelligence (XAI 2018)
K. Čyras, X. Fan, C. Schulz, F. Toni: Assumption-Based Argumentation: Disputes, Explanations, Preferences
Handbook Of Formal Argumentation volume 1, 2018
IfCoLoG Journal of Logics and their Applications 2017 September
K. Čyras, C. Schulz, F. Toni: Capturing Bipolar Argumentation in Non-flat Assumption-Based Argumentation
The 20^th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2017)
Z. Bao, K. Čyras, F. Toni: ABAplus: Attack Reversal in Abstract and Structured Argumentation with Preferences
The 20^th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2017)
K. Čyras: Rational versus Intuitive Outcomes of Reasoning with Preferences: Argumentation Perspective
Iberoamerican Journal of Artificial Intelligence 2017 March
K. Čyras, F. Toni: ABA+: Assumption-Based Argumentation with Preferences
The 15^th International Conference on Principles of Knowledge Representation and Reasoning (KR 2016)
K. Čyras, K. Satoh, F. Toni: Abstract Argumentation for Case-Based Reasoning
The 15^th International Conference on Principles of Knowledge Representation and Reasoning (KR 2016)
K. Čyras, F. Toni: Properties of ABA+ for Non-Monotonic Reasoning
The 16^th International Workshop on Non-Monotonic Reasoning (NMR 2016)
K. Čyras, K. Satoh, F. Toni: Explanation for Case-Based Reasoning via Abstract Argumentation
The 6^th International Conference on Computational Models of Argument (COMMA 2016)
A. Rago, K. Čyras, F. Toni: Adapting the DF-QuAD Algorithm to Bipolar Argumentation
Workshop on Systems and Algorithms for Formal Argumentation (SAFA 2016)
K. Čyras: Argumentation-based Reasoning with Preferences
Workshop on Decision Making in Dynamic Information Environments (DeMaDIE) at the 17^th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2016)
K. Čyras, F. Toni: Non-Monotonic Inference Properties for Assumption-Based Argumentation
The 2015 International Workshop on Theory and Applications of Formal Argument (TAFA 2015)

Invited Talks

Argumentation-enabled AI Appplications
Theory Group seminar, Swansea University (21 March 2019)
AI for Complex Clinical Decision Support
The Forum: AI & Health, Imperial College London (1 March 2019)
Explaining Predictions from Data Argumentatively
Explain AI@Imperial Workshop, Imperial College London (25 April 2018)
Structured Argumentation with Preferences: The ABA+ Formalism. (ABA+ and Weak Contraposition)
Individual and Collective Reasoning group seminar, University of Luxembourg (14 October 2016)
AA-CBR: Abstract Argumentation for Case-Based Reasoning
National Institute of Informatics, Tokyo, Japan (17 May 2016)
ABA+: Assumption-Based Argumentation with Preferences
Agents and Intelligent Systems (AIS) group seminar, King's College London (20 April 2016)
Non-monotonic Logic
Tomorrow's Mathematicians Today (TMT) 2014 Conference, University of Surrey (15 February 2014)

Posters

K. Čyras, T. Oliveira: Resolving Conflicts in Clinical Guidelines using Argumentation
AAMAS 2019
K. Čyras, T. Oliveira: Argumentation for Reasoning with Conflicting Clinical Guidelines and Preferences
KR 2018
O. Cocarascu, K. Čyras, F. Toni: Explanatory Predictions with Artificial Neural Networks and Argumentation
XAI 2018
K. Čyras, F. Toni: ABA+: Assumption-Based Argumentation with Preferences
KR 2016
K. Čyras, K. Satoh, F. Toni: Abstract Argumentation for Case-Based Reasoning
KR 2016
K. Čyras: Assumption-Based Argumentation with Preferences
Google PhD Poster Competition, Department of Computing, Imperial College London