Main

Interests

Main.Interests History

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January 20, 2015, at 03:14 PM by 129.215.164.102 -
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Recently, I have become more interested in hybrid man-machine collective intelligence, with two focal areas: social computation, and the evolution of meaning. In social computation, I am interested in how large collectives of collaborating humans and software agents can solve problems on the Web that are too complex for humans or machines to solve by themselves. In research on the evolution of meaning, I am investigating how artificial agents can benefit from the mechanisms humans use in negotiating the meaning of what they communicate with each other in order to improve the interoperability of distributed systems, but also to understand the social foundation of collective intelligence.''

to:

Recently, I have become more interested in hybrid man-machine collective intelligence, with two focal areas: social computation, and the evolution of meaning. In social computation, I am interested in how large collectives of collaborating humans and software agents can solve problems on the Web that are too complex for humans or machines to solve by themselves. In research on the evolution of meaning, I am investigating how artificial agents can benefit from the mechanisms humans use in negotiating the meaning of what they communicate with each other in order to improve the interoperability of distributed systems, but also to understand the social foundation of collective intelligence''

January 20, 2015, at 03:13 PM by 129.215.164.102 -
January 20, 2015, at 03:13 PM by 129.215.164.102 -
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Michael Rovatsos

Multiagent systems and social computation.

''For the past 15 years, my research has been in multiagent systems, where most of my contributions have been in agent communication languages, multiagent planning and learning, trust and reputation, social reasoning, argumentation, and norms. Most of this work has focused on reasoning about interaction, more specifically the development of adaptive and scalable knowledge-based methods for reaching agreement, resolving conflict, and sharing knowledge among agents. My work uses mainly methods from symbolic AI such as automated planning, deductive reasoning and declarative approaches to systems modelling, but it has also involved such techniques as reinforcement learning and statistical reasoning. While I am interested in building rigorous models of intelligent reasoning and decision making, my research emphasises the importance of producing systems that work in practice.

Recently, I have become more interested in hybrid man-machine collective intelligence, with two focal areas: social computation, and the evolution of meaning. In social computation, I am interested in how large collectives of collaborating humans and software agents can solve problems on the Web that are too complex for humans or machines to solve by themselves. In research on the evolution of meaning, I am investigating how artificial agents can benefit from the mechanisms humans use in negotiating the meaning of what they communicate with each other in order to improve the interoperability of distributed systems, but also to understand the social foundation of collective intelligence.''

http://homepages.inf.ed.ac.uk/mrovatso


March 27, 2014, at 04:31 PM by 129.215.164.102 -
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Computational Nudging or How to alter a Human Agent's (HA) policy by controlling the information presented.

Utilizing a HA's learned preference model, we can guide his choice by adjusting the representation of alternatives in the feature space. Moreover, the presented alternatives can alter his perception of the feasibility of a future incentive, thus controlling its effectiveness.

to:

Computational Nudging or How to alter a Human Agent's (HA) policy by controlling the information presented.

Utilizing a HA's learned preference model, we can guide his choice by adjusting the representation of alternatives in the feature space. Moreover, the presented alternatives can alter his perception of the feasibility of a future incentive, thus controlling its effectiveness.

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Semantic Alignment of Heterogeneous Ontologies Induced from Sensor Data

My research is concerned with ontology alignment between heterogeneous ontologies where each ontology is induced independently from sensor measurements. We consider each disparate sensor/sensor cluster as an agent and all agents as a collaborative multi-agent system. As ontologies model a particular conceptualisation of a domain, for agents to exchange information about domain they must align ontologies. We are interested in the case that sharing domain knowledge improves a joint task performed by all agents and evidence for alignment takes the form of ontology samples exchanged between agents as messages in a coordinated communication game.

to:

Semantic Alignment of Heterogeneous Ontologies Induced from Sensor Data

My research is concerned with ontology alignment between heterogeneous ontologies where each ontology is induced independently from sensor measurements. We consider each disparate sensor/sensor cluster as an agent and all agents as a collaborative multi-agent system. As ontologies model a particular conceptualisation of a domain, for agents to exchange information about domain they must align ontologies. We are interested in the case that sharing domain knowledge improves a joint task performed by all agents and evidence for alignment takes the form of ontology samples exchanged between agents as messages in a coordinated communication game.

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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

Dimitris worked for his Ph D? on the analysis of algorithms in different variants of the Probably Approximately Correct model of learning (evolvability, multiple-instance learning, active learning), as well as on question answering with the aid of the commonsense knowledge base Concept Net? 4. Dimitris is currently working under the workpackage for compositionality and social orchestration in the Smart Society project and develops in parallel the relevant backend functionality of the server for the prototype of Smart Sharing.

to:

Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

Dimitris worked for his Ph D? on the analysis of algorithms in different variants of the Probably Approximately Correct model of learning (evolvability, multiple-instance learning, active learning), as well as on question answering with the aid of the commonsense knowledge base Concept Net? 4. Dimitris is currently working under the workpackage for compositionality and social orchestration in the Smart Society project and develops in parallel the relevant backend functionality of the server for the prototype of Smart Sharing.

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Agent-based Computational Economics of ‘Prosumer’ Organisations in Microgrids.

A Microgrid is a subsystem of a ‘Smarter’ electricity grid that integrates distributed energy resources (DER) and ICT in a localised distribution network. The dynamics of this system includes consumers who also produce electricity by their DER assets; these actors are known as ‘prosumers’ in the literature. Their assets can be distributed generation technologies (e.g., solar panels and wind turbines), domestic batteries and controllable loads, all of them managed by ‘smart’ controllers. This new dynamics of how electricity is to be produced and consumed poses some interesting challenges to balancing supply and demand in this complex dynamic system.

Therefore, organisations or clusters of prosumers can play an important role on coordinating many micro-resources in such a way it could be beneficial for a Microgrid so as to match supply with demand. The smart controllers are modelled as agents; they can compete or cooperate in a time-varying price electricity market. The main questions addressed are: (1) What are the determinants of organisational behaviour and performance given economic incentives? (2) How the prosumers’ skills matter to these organisations? And (3) how these organisations evolve? 

to:

Agent-based Computational Economics of ‘Prosumer’ Organisations in Microgrids.

''A Microgrid is a subsystem of a ‘Smarter’ electricity grid that integrates distributed energy resources (DER) and ICT in a localised distribution network. The dynamics of this system includes consumers who also produce electricity by their DER assets; these actors are known as ‘prosumers’ in the literature. Their assets can be distributed generation technologies (e.g., solar panels and wind turbines), domestic batteries and controllable loads, all of them managed by ‘smart’ controllers. This new dynamics of how electricity is to be produced and consumed poses some interesting challenges to balancing supply and demand in this complex dynamic system.

Therefore, organisations or clusters of prosumers can play an important role on coordinating many micro-resources in such a way it could be beneficial for a Microgrid so as to match supply with demand. The smart controllers are modelled as agents; they can compete or cooperate in a time-varying price electricity market. The main questions addressed are: (1) What are the determinants of organisational behaviour and performance given economic incentives? (2) How the prosumers’ skills matter to these organisations? And (3) how these organisations evolve? ''

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Content Creators and the Semantic Web

Behind the plethora of user-generated media content on the web are a multitude of content creators, actively pushing their creative works to a global audience. The activities, needs and desires of these content creators transcend the individual websites and communities they use. In order to answer questions about identity behaviours and social network dynamics on a large scale, as well as to build applications that can facilitate collaboration between content creators, I am working to incorporate these creators and their works into the linked data cloud.

to:

Content Creators and the Semantic Web

Behind the plethora of user-generated media content on the web are a multitude of content creators, actively pushing their creative works to a global audience. The activities, needs and desires of these content creators transcend the individual websites and communities they use. In order to answer questions about identity behaviours and social network dynamics on a large scale, as well as to build applications that can facilitate collaboration between content creators, I am working to incorporate these creators and their works into the linked data cloud.

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Communication Planning

Humans are not sole entities but social beings that can accomplish more working together than by themselves. This is only possible because humans are able to communicate and agree on what to do together. In the "Communication Planning" project (WP 3?/ESSENCE), we are interested in modelling this behaviour for autonomous and independent agents in a way that they will be able to communicate with a different agent or human without knowing their internal structure. In a few words, given a complex task environment, what kind of planning activity should an agent do to decide what should it say to whom in order to accomplish its goals.

to:

Communication Planning

Humans are not sole entities but social beings that can accomplish more working together than by themselves. This is only possible because humans are able to communicate and agree on what to do together. In the "Communication Planning" project (WP 3?/ESSENCE), we are interested in modelling this behaviour for autonomous and independent agents in a way that they will be able to communicate with a different agent or human without knowing their internal structure. In a few words, given a complex task environment, what kind of planning activity should an agent do to decide what should it say to whom in order to accomplish its goals.

March 27, 2014, at 04:29 PM by 129.215.164.102 -
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Key Words: Incentives, behavioural modelling, recommender systems, human Behaviour modelling (learning preferences, designing Incentives, and nudging)

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Interests: Incentives, behavioural modelling, recommender systems, human Behaviour modelling (learning preferences, designing Incentives, and nudging)

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Language Games, Ontology Grounding, Ontology Matching, Ontology Negotiation

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Interests: Language Games, Ontology Grounding, Ontology Matching, Ontology Negotiation

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Keywords: semantic web, user-generated content, content creators, linked data, linked media, social network analysis, social machines.

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Interests: semantic web, user-generated content, content creators, linked data, linked media, social network analysis, social machines.

March 27, 2014, at 04:27 PM by 129.215.164.102 -
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Computational Nudging or How to alter a Human Agent's (HA) policy by controlling the information presented.

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Computational Nudging or How to alter a Human Agent's (HA) policy by controlling the information presented.

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Key Words: Incentives, behavioural modelling, recommender systems, human Behaviour modelling (learning preferences, designing Incentives, and nudging)

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Semantic Alignment of Heterogeneous Ontologies Induced from Sensor Data

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Semantic Alignment of Heterogeneous Ontologies Induced from Sensor Data

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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

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Agent-based Computational Economics of ‘Prosumer’ Organisations in Microgrids.

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Agent-based Computational Economics of ‘Prosumer’ Organisations in Microgrids.

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Content Creators and the Semantic Web

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Content Creators and the Semantic Web

March 27, 2014, at 04:24 PM by 129.215.164.102 -
March 27, 2014, at 04:22 PM by 129.215.164.102 -
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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

March 27, 2014, at 04:21 PM by 129.215.164.102 -
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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

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Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

March 27, 2014, at 04:19 PM by 129.215.164.102 -
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The people who are attending regularly the seminar have the following areas of expertise and broader interests.

nameexpertisebroader interests
Andreadis, Pavlosqueueing theory, machine learningincentives, behavioural modelling, recommender systems, human Behaviour modelling (learning preferences, designing Incentives, and nudging)
Anslow, Michaelsymbolic grounding, language games, ontologiessensor nets, sensor fusion, machine learning, cognitive science
Bova, NicolaTBATBA
Diochnos, Dimitrislearning, reasoning (question-answering)knowledge bases, network analysis, evolution
Elizondo, Sergiomarket-based prosumer coordination for future electricity networkscomplex adaptive systems, game theory
Guhe, Markuscognitive modelling, natural language dialoguecognitive science
Guy, Amysemantic web, social informaticsnetwork analysis, provenance
Lascarides, Alexnatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Manataki, Aretiworkflow modelling, simulation analysis (distributed systems)knowledge base systems, argumentation and application areas
Marques, TâniaTBATBA
Motta, Gustavodistributed systems, security on health informaticstele-radiology and new methods, complex adaptive systems
Murray-Rust, DaveTBATBA
Papapanagiotou, Petrosprocess modelling and formal verificationconcurrent systems, semantic web
Queiroz, Natashaplanning applications on knowledge bases, semantic web conceptshealth informatics, collaborative systems
Rovatsos, Michaelmultiagent systems, especially planning, communication and learningsocial computation, negotiation and evolution of meaning
Yang, GuoliRUAOE modelling (symbolic)network dynamics, evolutionary game theory
to:

Pavlos Andreadis

Computational Nudging or How to alter a Human Agent's (HA) policy by controlling the information presented.

Utilizing a HA's learned preference model, we can guide his choice by adjusting the representation of alternatives in the feature space. Moreover, the presented alternatives can alter his perception of the feasibility of a future incentive, thus controlling its effectiveness.

http://www.inf.ed.ac.uk/people/students/Pavlos_Andreadis.html


Michael Anslow

Semantic Alignment of Heterogeneous Ontologies Induced from Sensor Data

My research is concerned with ontology alignment between heterogeneous ontologies where each ontology is induced independently from sensor measurements. We consider each disparate sensor/sensor cluster as an agent and all agents as a collaborative multi-agent system. As ontologies model a particular conceptualisation of a domain, for agents to exchange information about domain they must align ontologies. We are interested in the case that sharing domain knowledge improves a joint task performed by all agents and evidence for alignment takes the form of ontology samples exchanged between agents as messages in a coordinated communication game.

Language Games, Ontology Grounding, Ontology Matching, Ontology Negotiation

http://homepages.inf.ed.ac.uk/s1145173/


Dimitris Diochnos

Compositionality and social orchestration in the Smart Society project and the Smart Sharing application

Dimitris worked for his Ph D? on the analysis of algorithms in different variants of the Probably Approximately Correct model of learning (evolvability, multiple-instance learning, active learning), as well as on question answering with the aid of the commonsense knowledge base Concept Net? 4. Dimitris is currently working under the workpackage for compositionality and social orchestration in the Smart Society project and develops in parallel the relevant backend functionality of the server for the prototype of Smart Sharing.

http://homepages.inf.ed.ac.uk/ddiochno/


Sergio Elizondo Gonzalez

Agent-based Computational Economics of ‘Prosumer’ Organisations in Microgrids.

A Microgrid is a subsystem of a ‘Smarter’ electricity grid that integrates distributed energy resources (DER) and ICT in a localised distribution network. The dynamics of this system includes consumers who also produce electricity by their DER assets; these actors are known as ‘prosumers’ in the literature. Their assets can be distributed generation technologies (e.g., solar panels and wind turbines), domestic batteries and controllable loads, all of them managed by ‘smart’ controllers. This new dynamics of how electricity is to be produced and consumed poses some interesting challenges to balancing supply and demand in this complex dynamic system.

Therefore, organisations or clusters of prosumers can play an important role on coordinating many micro-resources in such a way it could be beneficial for a Microgrid so as to match supply with demand. The smart controllers are modelled as agents; they can compete or cooperate in a time-varying price electricity market. The main questions addressed are: (1) What are the determinants of organisational behaviour and performance given economic incentives? (2) How the prosumers’ skills matter to these organisations? And (3) how these organisations evolve?     

https://www.inf.ed.ac.uk/people/students/Sergio_Elizondo_Gonzalez.html


Amy Guy

Content Creators and the Semantic Web

Behind the plethora of user-generated media content on the web are a multitude of content creators, actively pushing their creative works to a global audience. The activities, needs and desires of these content creators transcend the individual websites and communities they use. In order to answer questions about identity behaviours and social network dynamics on a large scale, as well as to build applications that can facilitate collaboration between content creators, I am working to incorporate these creators and their works into the linked data cloud.

Keywords: semantic web, user-generated content, content creators, linked data, linked media, social network analysis, social machines.

http://rhiaro.co.uk


Tania Marques

Communication Planning

Humans are not sole entities but social beings that can accomplish more working together than by themselves. This is only possible because humans are able to communicate and agree on what to do together. In the "Communication Planning" project (WP 3?/ESSENCE), we are interested in modelling this behaviour for autonomous and independent agents in a way that they will be able to communicate with a different agent or human without knowing their internal structure. In a few words, given a complex task environment, what kind of planning activity should an agent do to decide what should it say to whom in order to accomplish its goals.

http://www.inf.ed.ac.uk/people/staff/Tania_Marques.html

March 27, 2014, at 04:09 PM by 129.215.164.102 -
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Andreadis, Pavlosqueueing theory, machine learningincentives, behavioural modelling
to:
Andreadis, Pavlosqueueing theory, machine learningincentives, behavioural modelling, recommender systems, human Behaviour modelling (learning preferences, designing Incentives, and nudging)
February 26, 2014, at 03:40 PM by Dimitris - another correction on the accent used in Tânia's name
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Marques, TaniaTBATBA
to:
Marques, TâniaTBATBA
February 10, 2014, at 10:14 PM by Dimitris - Added Tania and Nicola to the list
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Bova, NicolaTBATBA
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Marques, TaniaTBATBA
January 27, 2014, at 09:49 PM by Dimitris - added interests for Sergio
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Elizondo, SergioTBATBA
to:
Elizondo, Sergiomarket-based prosumer coordination for future electricity networkscomplex adaptive systems, game theory
January 27, 2014, at 01:06 AM by Dimitris - Added Sergio to the list
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Elizondo, SergioTBATBA
January 14, 2014, at 04:32 PM by Michael Anslow -
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Anslow, Michaelsymbolic grounding, language games, ontologiessensor nets, machine learning, cognitive science
to:
Anslow, Michaelsymbolic grounding, language games, ontologiessensor nets, sensor fusion, machine learning, cognitive science
January 14, 2014, at 01:52 PM by Dimitris - Minor editing so that non-names and jargon are in lowercase letters
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NameExpertiseBroader Interests
Andreadis, PavlosQueueing theory, machine learningIncentives, behavioural modelling
Anslow, MichaelSymbolic grounding, language games, ontologiesSensor nets, machine learning, cognitive science
Diochnos, DimitrisLearning, reasoning (question-answering)Knowledge bases, network analysis, evolution
Guhe, MarkusCognitive modelling, natural language dialogueCognitive science
Guy, AmySemantic web, social informaticsNetwork analysis, provenance
Lascarides, AlexNatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Manataki, AretiWorkflow modelling, simulation analysis (distributed systems)Knowledge base systems, argumentation and application areas
Motta, GustavoDistributed systems, security on health informaticsTele-radiology and new methods, complex adaptive systems
to:
nameexpertisebroader interests
Andreadis, Pavlosqueueing theory, machine learningincentives, behavioural modelling
Anslow, Michaelsymbolic grounding, language games, ontologiessensor nets, machine learning, cognitive science
Diochnos, Dimitrislearning, reasoning (question-answering)knowledge bases, network analysis, evolution
Guhe, Markuscognitive modelling, natural language dialoguecognitive science
Guy, Amysemantic web, social informaticsnetwork analysis, provenance
Lascarides, Alexnatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Manataki, Aretiworkflow modelling, simulation analysis (distributed systems)knowledge base systems, argumentation and application areas
Motta, Gustavodistributed systems, security on health informaticstele-radiology and new methods, complex adaptive systems
Changed lines 14-15 from:
Papapanagiotou, PetrosProcess modelling and formal verificationConcurrent systems, semantic web
Queiroz, NatashaPlanning applications on knowledge bases, semantic web conceptsHealth informatics, collaborative systems
to:
Papapanagiotou, Petrosprocess modelling and formal verificationconcurrent systems, semantic web
Queiroz, Natashaplanning applications on knowledge bases, semantic web conceptshealth informatics, collaborative systems
Changed line 17 from:
Yang, GuoliRUAOE modelling (symbolic)Network dynamics, evolutionary game theory
to:
Yang, GuoliRUAOE modelling (symbolic)network dynamics, evolutionary game theory
January 14, 2014, at 01:46 PM by Dimitris -
Changed line 5 from:
Andreadis, PavlosQueueing theory, machine learningIncentives, behavioural medelling
to:
Andreadis, PavlosQueueing theory, machine learningIncentives, behavioural modelling
January 14, 2014, at 01:45 PM by Dimitris -
Changed lines 5-17 from:
Pavlos AndreadisQueueing theory, machine learningIncentives, behavioural medelling
Michael AnslowSymbolic grounding, language games, ontologiesSensor nets, machine learning, cognitive science
Dimitris DiochnosLearning, reasoning (question-answering)Knowledge bases, network analysis, evolution
Markus GuheCognitive modelling, natural language dialogueCognitive science
Amy GuySemantic web, social informaticsNetwork analysis, provenance
Alex LascaridesNatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Areti ManatakiWorkflow modelling, simulation analysis (distributed systems)Knowledge base systems, argumentation and application areas
Gustavo MottaDistributed systems, security on health informaticsTele-radiology and new methods, complex adaptive systems
Dave Murray-RustTBATBA
Petros PapapanagiotouProcess modelling and formal verificationConcurrent systems, semantic web
Natasha QueirozPlanning applications on knowledge bases, semantic web conceptsHealth informatics, collaborative systems
Michael Rovatsosmultiagent systems, especially planning, communication and learningsocial computation, negotiation and evolution of meaning
Guoli YangRUAOE modelling (symbolic)Network dynamics, evolutionary game theory
to:
Andreadis, PavlosQueueing theory, machine learningIncentives, behavioural medelling
Anslow, MichaelSymbolic grounding, language games, ontologiesSensor nets, machine learning, cognitive science
Diochnos, DimitrisLearning, reasoning (question-answering)Knowledge bases, network analysis, evolution
Guhe, MarkusCognitive modelling, natural language dialogueCognitive science
Guy, AmySemantic web, social informaticsNetwork analysis, provenance
Lascarides, AlexNatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Manataki, AretiWorkflow modelling, simulation analysis (distributed systems)Knowledge base systems, argumentation and application areas
Motta, GustavoDistributed systems, security on health informaticsTele-radiology and new methods, complex adaptive systems
Murray-Rust, DaveTBATBA
Papapanagiotou, PetrosProcess modelling and formal verificationConcurrent systems, semantic web
Queiroz, NatashaPlanning applications on knowledge bases, semantic web conceptsHealth informatics, collaborative systems
Rovatsos, Michaelmultiagent systems, especially planning, communication and learningsocial computation, negotiation and evolution of meaning
Yang, GuoliRUAOE modelling (symbolic)Network dynamics, evolutionary game theory
January 14, 2014, at 01:41 PM by Dimitris - Added information with peoples' interests
Added lines 1-17:

The people who are attending regularly the seminar have the following areas of expertise and broader interests.

NameExpertiseBroader Interests
Pavlos AndreadisQueueing theory, machine learningIncentives, behavioural medelling
Michael AnslowSymbolic grounding, language games, ontologiesSensor nets, machine learning, cognitive science
Dimitris DiochnosLearning, reasoning (question-answering)Knowledge bases, network analysis, evolution
Markus GuheCognitive modelling, natural language dialogueCognitive science
Amy GuySemantic web, social informaticsNetwork analysis, provenance
Alex LascaridesNatural language semantics, commonsense reasoning, games in extended form, CP-NetsInteraction and human action and decision making
Areti ManatakiWorkflow modelling, simulation analysis (distributed systems)Knowledge base systems, argumentation and application areas
Gustavo MottaDistributed systems, security on health informaticsTele-radiology and new methods, complex adaptive systems
Dave Murray-RustTBATBA
Petros PapapanagiotouProcess modelling and formal verificationConcurrent systems, semantic web
Natasha QueirozPlanning applications on knowledge bases, semantic web conceptsHealth informatics, collaborative systems
Michael Rovatsosmultiagent systems, especially planning, communication and learningsocial computation, negotiation and evolution of meaning
Guoli YangRUAOE modelling (symbolic)Network dynamics, evolutionary game theory

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