AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2023
Cossentino, Massimo; Sabatucci, Luca; Mylopoulos, John
Consciousness as a Trigger to Adaptation Journal Article
In: Journal of Artificial Intelligence and Consciousness, vol. 20, no. 1, pp. 27–47, 2023.
Abstract | Links | BibTeX | Tags: Agents, Consciousness, Goal-Oriented Approach, Goals, Practical Reasoning, Self-Consciousness
@article{cossentinoConsciousnessTriggerAdaptation2023,
title = {Consciousness as a Trigger to Adaptation},
author = { Massimo Cossentino and Luca Sabatucci and John Mylopoulos},
doi = {10.1142/S270507852250014X},
year = {2023},
date = {2023-01-01},
journal = {Journal of Artificial Intelligence and Consciousness},
volume = {20},
number = {1},
pages = {27--47},
abstract = {Consciousness refers to mental states of a cognitive agent that make it aware of elements of its environment and its own state.Phenomena of consciousness have been studied in Philosophy, Psychology and Cognitive Science. With the advent of Artificial Intelligence (AI) the study of consciousness has broadened to include questions such as textbackslash textbackslashvirgWhen is an AI system conscious?, textbackslash textbackslashvirgWhat role does consciousness play in the cognitive architecture of an AI system?. This paper proposes a cognitive architecture that attempts to answer such questions and is an extension of proposals for practical reasoning, founded on the notion of epistemic goals, goals where the desired state-of-affairs is knowledge of something in the environment or within the agent itself. The proposal is illustrated with an example involving an autonomous vehicle.},
keywords = {Agents, Consciousness, Goal-Oriented Approach, Goals, Practical Reasoning, Self-Consciousness},
pubstate = {published},
tppubtype = {article}
}
Consciousness refers to mental states of a cognitive agent that make it aware of elements of its environment and its own state.Phenomena of consciousness have been studied in Philosophy, Psychology and Cognitive Science. With the advent of Artificial Intelligence (AI) the study of consciousness has broadened to include questions such as textbackslash textbackslashvirgWhen is an AI system conscious?, textbackslash textbackslashvirgWhat role does consciousness play in the cognitive architecture of an AI system?. This paper proposes a cognitive architecture that attempts to answer such questions and is an extension of proposals for practical reasoning, founded on the notion of epistemic goals, goals where the desired state-of-affairs is knowledge of something in the environment or within the agent itself. The proposal is illustrated with an example involving an autonomous vehicle.
Cossentino, Massimo; Sabatucci, Luca; Mylopoulos, John
Consciousness as a Trigger to Adaptation Journal Article
In: Journal of Artificial Intelligence and Consciousness, vol. 20, no. 1, pp. 27–47, 2023.
Abstract | Links | BibTeX | Tags: Agents, Consciousness, Goal-Oriented Approach, Goals, Practical Reasoning, Self-Consciousness
@article{cossentino_consciousness_2023,
title = {Consciousness as a Trigger to Adaptation},
author = {Massimo Cossentino and Luca Sabatucci and John Mylopoulos},
doi = {10.1142/S270507852250014X},
year = {2023},
date = {2023-01-01},
journal = {Journal of Artificial Intelligence and Consciousness},
volume = {20},
number = {1},
pages = {27–47},
abstract = {Consciousness refers to mental states of a cognitive agent that make it aware of elements of its environment and its own state.Phenomena of consciousness have been studied in Philosophy, Psychology and Cognitive Science. With the advent of Artificial Intelligence (AI) the study of consciousness has broadened to include questions such as textbackslashtextbackslashvirgWhen is an AI system conscious?, textbackslashtextbackslashvirgWhat role does consciousness play in the cognitive architecture of an AI system?. This paper proposes a cognitive architecture that attempts to answer such questions and is an extension of proposals for practical reasoning, founded on the notion of epistemic goals, goals where the desired state-of-affairs is knowledge of something in the environment or within the agent itself. The proposal is illustrated with an example involving an autonomous vehicle.},
keywords = {Agents, Consciousness, Goal-Oriented Approach, Goals, Practical Reasoning, Self-Consciousness},
pubstate = {published},
tppubtype = {article}
}
Consciousness refers to mental states of a cognitive agent that make it aware of elements of its environment and its own state.Phenomena of consciousness have been studied in Philosophy, Psychology and Cognitive Science. With the advent of Artificial Intelligence (AI) the study of consciousness has broadened to include questions such as textbackslashtextbackslashvirgWhen is an AI system conscious?, textbackslashtextbackslashvirgWhat role does consciousness play in the cognitive architecture of an AI system?. This paper proposes a cognitive architecture that attempts to answer such questions and is an extension of proposals for practical reasoning, founded on the notion of epistemic goals, goals where the desired state-of-affairs is knowledge of something in the environment or within the agent itself. The proposal is illustrated with an example involving an autonomous vehicle.
2019
Sabatucci, Luca; Cossentino, Massimo
Supporting Dynamic Workflows with Automatic Extraction of Goals from BPMN Journal Article
In: ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol. 14, no. 2, pp. 1–38, 2019.
Abstract | Links | BibTeX | Tags: Automatic extraction, Business Process, Dynamic workflow, Goals, Self-Adaptive Systems
@article{sabatucciSupportingDynamicWorkflows2019,
title = {Supporting Dynamic Workflows with Automatic Extraction of Goals from BPMN},
author = { Luca Sabatucci and Massimo Cossentino},
doi = {10.1145/3355488},
year = {2019},
date = {2019-01-01},
journal = {ACM Transactions on Autonomous and Adaptive Systems (TAAS)},
volume = {14},
number = {2},
pages = {1--38},
abstract = {Organizations willing to employ workflow technology have to be prepared to undertake a significant investment of time and effort due to the exceptional dynamic nature of the business environment. Today, it is unlikely that processes are modeled once to be repeatedly executed without any changes. Goal-oriented dynamic workflows are a promising approach to provide flexibility to the execution of business processes. Many goal-oriented frameworks exist in literature to be used for the purpose. However, modeling goals is a burden for the business analyst. This work proposes an automatic approach for extracting goals from a business process for supporting adaptive workflows. The approach consists of a static analysis of the global workflow state. Goals derive from individual BPMN elements and their interactions. For validating the theory, we developed the BPMN2Goals tool, which has been used for supporting a middleware for self-adaptation.},
keywords = {Automatic extraction, Business Process, Dynamic workflow, Goals, Self-Adaptive Systems},
pubstate = {published},
tppubtype = {article}
}
Organizations willing to employ workflow technology have to be prepared to undertake a significant investment of time and effort due to the exceptional dynamic nature of the business environment. Today, it is unlikely that processes are modeled once to be repeatedly executed without any changes. Goal-oriented dynamic workflows are a promising approach to provide flexibility to the execution of business processes. Many goal-oriented frameworks exist in literature to be used for the purpose. However, modeling goals is a burden for the business analyst. This work proposes an automatic approach for extracting goals from a business process for supporting adaptive workflows. The approach consists of a static analysis of the global workflow state. Goals derive from individual BPMN elements and their interactions. For validating the theory, we developed the BPMN2Goals tool, which has been used for supporting a middleware for self-adaptation.
Sabatucci, Luca; Cossentino, Massimo
Supporting dynamic workflows with automatic extraction of goals from BPMN Journal Article
In: ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol. 14, no. 2, pp. 1–38, 2019.
Abstract | Links | BibTeX | Tags: Automatic extraction, Business Process, Dynamic workflow, Goals, Self-Adaptive Systems
@article{sabatucci_supporting_2019,
title = {Supporting dynamic workflows with automatic extraction of goals from BPMN},
author = {Luca Sabatucci and Massimo Cossentino},
doi = {10.1145/3355488},
year = {2019},
date = {2019-01-01},
journal = {ACM Transactions on Autonomous and Adaptive Systems (TAAS)},
volume = {14},
number = {2},
pages = {1–38},
abstract = {Organizations willing to employ workflow technology have to be prepared to undertake a significant investment of time and effort due to the exceptional dynamic nature of the business environment. Today, it is unlikely that processes are modeled once to be repeatedly executed without any changes. Goal-oriented dynamic workflows are a promising approach to provide flexibility to the execution of business processes. Many goal-oriented frameworks exist in literature to be used for the purpose. However, modeling goals is a burden for the business analyst. This work proposes an automatic approach for extracting goals from a business process for supporting adaptive workflows. The approach consists of a static analysis of the global workflow state. Goals derive from individual BPMN elements and their interactions. For validating the theory, we developed the BPMN2Goals tool, which has been used for supporting a middleware for self-adaptation.},
keywords = {Automatic extraction, Business Process, Dynamic workflow, Goals, Self-Adaptive Systems},
pubstate = {published},
tppubtype = {article}
}
Organizations willing to employ workflow technology have to be prepared to undertake a significant investment of time and effort due to the exceptional dynamic nature of the business environment. Today, it is unlikely that processes are modeled once to be repeatedly executed without any changes. Goal-oriented dynamic workflows are a promising approach to provide flexibility to the execution of business processes. Many goal-oriented frameworks exist in literature to be used for the purpose. However, modeling goals is a burden for the business analyst. This work proposes an automatic approach for extracting goals from a business process for supporting adaptive workflows. The approach consists of a static analysis of the global workflow state. Goals derive from individual BPMN elements and their interactions. For validating the theory, we developed the BPMN2Goals tool, which has been used for supporting a middleware for self-adaptation.
2012
Cossentino, Massimo; Lodato, Carmelo; Lopes, Salvatore; Ribino, Patrizia; Sabatucci, Luca; Seidita, Valeria; others,
The Role of Ontology in Agent-Oriented Requirements Analysis Proceedings Article
In: In Proceedings of the 10th European Workshop on Multi-Agent Systems, EUMAS 2012, pp. 88–102, 2012.
Abstract | BibTeX | Tags: Goal-Oriented Approach, Goals, Multi agent systems, Semantic layer
@inproceedings{cossentinoRoleOntologyAgentOriented2012,
title = {The Role of Ontology in Agent-Oriented Requirements Analysis},
author = { Massimo Cossentino and Carmelo Lodato and Salvatore Lopes and Patrizia Ribino and Luca Sabatucci and Valeria Seidita and others},
year = {2012},
date = {2012-01-01},
booktitle = {In Proceedings of the 10th European Workshop on Multi-Agent Systems, EUMAS 2012},
pages = {88--102},
abstract = {Goals identification is an open issue in the Requirement Analysis field for Multi-Agent System design. Stakeholders commonly don't have full and exhaustive awareness about their real objectives in the domain problem. Goals are implicitly expressed during the inquiring phase. Thus, the goal identification task is commonly ascribed to the expertise of the analyst. In this work we propose a new methodological approach to formalize the problem domain in terms of its ontological representation. We also introduce a new heuristic for extraction and val- idation of goals from the problem description. In this approach the do- main can provide evidences for the identification of unvoiced goals and for their validation according to the contextual data.},
keywords = {Goal-Oriented Approach, Goals, Multi agent systems, Semantic layer},
pubstate = {published},
tppubtype = {inproceedings}
}
Goals identification is an open issue in the Requirement Analysis field for Multi-Agent System design. Stakeholders commonly don't have full and exhaustive awareness about their real objectives in the domain problem. Goals are implicitly expressed during the inquiring phase. Thus, the goal identification task is commonly ascribed to the expertise of the analyst. In this work we propose a new methodological approach to formalize the problem domain in terms of its ontological representation. We also introduce a new heuristic for extraction and val- idation of goals from the problem description. In this approach the do- main can provide evidences for the identification of unvoiced goals and for their validation according to the contextual data.
Cossentino, Massimo; Lodato, Carmelo; Lopes, Salvatore; Ribino, Patrizia; Sabatucci, Luca; Seidita, Valeria; others,
The Role of Ontology in Agent-Oriented Requirements Analysis Proceedings Article
In: In Proceedings of the 10th European Workshop on Multi-Agent Systems, EUMAS 2012, pp. 88–102, 2012.
Abstract | Links | BibTeX | Tags: Goal-Oriented Approach, Goals, Multi agent systems, Semantic layer
@inproceedings{cossentino_role_2012,
title = {The Role of Ontology in Agent-Oriented Requirements Analysis},
author = {Massimo Cossentino and Carmelo Lodato and Salvatore Lopes and Patrizia Ribino and Luca Sabatucci and Valeria Seidita and others},
url = {https://www.semanticscholar.org/paper/The-Role-of-Ontology-in-Agent-Oriented-Requirements-Cossentino-Lodato/f1dfb0aa89fdec4ffc0102517485fca9cf5f4fe2},
year = {2012},
date = {2012-01-01},
booktitle = {In Proceedings of the 10th European Workshop on Multi-Agent Systems, EUMAS 2012},
pages = {88–102},
abstract = {Goals identification is an open issue in the Requirement Analysis field for Multi-Agent System design. Stakeholders commonly don’t have full and exhaustive awareness about their real objectives in the domain problem. Goals are implicitly expressed during the inquiring phase. Thus, the goal identification task is commonly ascribed to the expertise of the analyst. In this work we propose a new methodological approach to formalize the problem domain in terms of its ontological representation. We also introduce a new heuristic for extraction and val- idation of goals from the problem description. In this approach the do- main can provide evidences for the identification of unvoiced goals and for their validation according to the contextual data.},
keywords = {Goal-Oriented Approach, Goals, Multi agent systems, Semantic layer},
pubstate = {published},
tppubtype = {inproceedings}
}
Goals identification is an open issue in the Requirement Analysis field for Multi-Agent System design. Stakeholders commonly don’t have full and exhaustive awareness about their real objectives in the domain problem. Goals are implicitly expressed during the inquiring phase. Thus, the goal identification task is commonly ascribed to the expertise of the analyst. In this work we propose a new methodological approach to formalize the problem domain in terms of its ontological representation. We also introduce a new heuristic for extraction and val- idation of goals from the problem description. In this approach the do- main can provide evidences for the identification of unvoiced goals and for their validation according to the contextual data.