- Carles Sierra is Vice-Director of the Artificial Intelligence Research Institute (IIIA) of the Spanish National Resea... moreCarles Sierra is Vice-Director of the Artificial Intelligence Research Institute (IIIA) of the Spanish National Research Council (CSIC) located in the area of Barcelona. He has been contributing to Artificial Intelligence research since 1985 in the areas of Knowledge Representation, Auctions, Electronic Institutions, Autonomous Agents and Multiagent Systems, and Agreement Technologies. He has participated in more than 20 EU funded projects, is or has been member of several journal editorial boards including AIJ and JAIR and is the editor-in-chief of the JAAMAS journal. He ha published more than 400 papers that have received 17000 citations. He organised IJCAI in 2011 in Barcelona and was the Program Chair of IJCAI 2017 in Melbourne. He is an EurAI Fellow.edit
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Report Version: final Report Preparation Date: 30.1.2007 Classification: deliverable D4.7
In this chapter we introduce the PeerLearn methodology and its associated tools. We base the design of pedagogical workflows for students on the definition of rubrics (using PeerAssess) as the starting element that drives the creation of... more
In this chapter we introduce the PeerLearn methodology and its associated tools. We base the design of pedagogical workflows for students on the definition of rubrics (using PeerAssess) as the starting element that drives the creation of lesson plans (using LessonEditor). These plans run over our web platform (Peer-Flow). Students can evaluate one another following given rubrics and teachers can accept (or not) marks produced by a collaborative assessment tool (COMAS). Experimental results show that PeerLearn provide students with a highly satisfying new pedagogical experience and increased learning outcomes. Source URL: https://www.iiia.csic.es/en/node/54265 Links [1] https://www.iiia.csic.es/en/staff/ismel-brito [2] https://www.iiia.csic.es/en/staff/patricia-gutierrez [3] https://www.iiia.csic.es/en/bibliography?f[author]=108 [4] https://www.iiia.csic.es/en/staff/dave-de-jonge [5] https://www.iiia.csic.es/en/staff/lissette-lemus [6] https://www.iiia.csic.es/en/staff/nardine-osman ...
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Research Interests: Information Systems, Computer Science, Multiagent Systems, E Business, Community Involvement, and 15 moreRole-playing Game Theory, Multi Agent System, Virtual Reality, Computer Games, Multi Agent Systems, Information Sources, Gaming technology, Business Game, Online Community, Game Engine, Business environment, Role Models, Facilitator, D, and Electronic Commerce
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Research Interests: Cognitive Science, Computer Science, Artificial Intelligence, Human Computer Interaction, Visualization, and 15 moreHuman Factors, Tourism, Multi Agent System, Virtual Reality, Software Agents, Graphics, Avatar, Geomatic Engineering, Visualisation, Game Engine, Software Agent, Transaction Processing, Foot, Graphical User Interface, and Information System
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The advancement of technologies for autonomous vehicles (AVs) provides great potential for intelligent traffic control and management in the future. The deployment of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and... more
The advancement of technologies for autonomous vehicles (AVs) provides great potential for intelligent traffic control and management in the future. The deployment of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) communications enable traffic control on road segments, intersections or regional road networks with more options, either centralized or decentralized. However, choosing these options is not purely technical but a trade-off between autonomous decision-making and system optimization. One useful quantitative criterion for such a trade-off is the price of anarchy (PoA) of autonomous decision-making. This paper analyses the price of anarchy for road networks with traffic of autonomous vehicles. We model a traffic network as a routing game in which vehicles are selfish agents who choose routes to travel autonomously to minimize travel delays caused by road congestion. Unlike existing research in which the latency function of road conge...
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Trust and reputation measures are crucial in distributed open systems where agents need to decide whom or what to choose. Existing work has overlooked the impact of an entity's position in its structural graph and its effect on the... more
Trust and reputation measures are crucial in distributed open systems where agents need to decide whom or what to choose. Existing work has overlooked the impact of an entity's position in its structural graph and its effect on the propagation of trust in such graphs. This paper presents an algorithm for the propagation of rep- utation in structural graphs. It allows agents to infer their opinion about unfamiliar entities based on their view of related entities. The proposed mechanism focuses on the "part of" relation to illustrate how reputation may flow (or propagate) from one entity to another. The paper bases its reputation measures on opinions, which it defines as probability distributions over an evaluation space, providing a rich representation of opinions.
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This article addresses the problem of finding suitable agents to collaborate with for a given interaction in distributed open systems, such as multiagent and P2P systems. The agent in question is given the chance to describe its... more
This article addresses the problem of finding suitable agents to collaborate with for a given interaction in distributed open systems, such as multiagent and P2P systems. The agent in question is given the chance to describe its confidence in its own capabilities. However, since agents may be malicious, misinformed, suffer from miscommunication, and so on, one also needs to calculate how much trusted is that agent. This article proposes a novel trust model that calculates the expectation about an agent's future performance in a given context by assessing both the agent's willingness and capability through the semantic comparison of the current context in question with the agent's performance in past similar experiences. The proposed mechanism for assessing trust may be applied to any real world application where past commitments are recorded and observations are made that assess these commitments, and the model can then calculate one's trust in another with respect t...
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Agreement Technologies are needed for autonomous agents to come to mutually acceptable agreements, typically on behalf of humans. These technologies include trust computing, negotiation, argumentation and semantic alignment. In this... more
Agreement Technologies are needed for autonomous agents to come to mutually acceptable agreements, typically on behalf of humans. These technologies include trust computing, negotiation, argumentation and semantic alignment. In this paper, we identify a number of open questions regarding the integration of computational models and tools for trust computing with negotiation, argumentation and semantic alignment. We consider these questions in general and in the context of applications in open, distributed settings such as the grid and cloud computing.
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The eRepLab is the name given to a set of tools and pieces of software that make possible the use an study of reputation mechanisms in the context of an electronic institution (eI). It has been designed and implemented principally to be a... more
The eRepLab is the name given to a set of tools and pieces of software that make possible the use an study of reputation mechanisms in the context of an electronic institution (eI). It has been designed and implemented principally to be a platform for the experiments performed in the framework of the eRep project (CIT5-028575, http://megatron. iiia. csic. es/eRep), however it is general enough to be used for any programmer and/or system designer that needs to integrate reputation and human agents in electronic institutions. ...
There are a number of available tools that support teachers in the management of lesson plans on the web. However, none of them is task-centred and support any form of lesson plan’s execution over the web. PeerLearn is an application that... more
There are a number of available tools that support teachers in the management of lesson plans on the web. However, none of them is task-centred and support any form of lesson plan’s execution over the web. PeerLearn is an application that allows both the design and the execution of lesson plans, where lesson plans are designed with respect to a selected rubric. PeerLearn uses electronic institutions to coordinate interactions, ensuring the rules set by the lesson plan are followed, and it relies on a trust-based model to calculate automated marks. The automated marks provide tremendous support for teachers when their online classrooms have massive numbers of students. This chapter provides an overview of the PeerLearn application, describes its underlying electronic institution, and presents a brief introduction to its automated assessment technology.
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We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action:NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to... more
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action:NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to test the algorithm we present a new variant of the Traveling Salesman Problem, in which there is not one, but many salesmen. The salesmen need to negotiate with each other in order to minimize the distances they have to cover. Finally we present the results of some tests we did with a simple implementation of the algorithm for
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When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Despite an increasingly networked world, technology falls short in supporting such daily tasks. u-Help provides a platform for... more
When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Despite an increasingly networked world, technology falls short in supporting such daily tasks. u-Help provides a platform for building a community of helpful people and supports them in finding volunteers for day-to-day tasks. It relies on three techniques that allow a requester and volunteer to find one another easily, and build up a community around such provision of services. First, we use an ontology to distinguish between the various tasks that u-Help allows people to provide. Second, a computational trust model is used to aggregate feedback from community members and allows people to discover who are good or bad at performing the various tasks. Last, a flooding algorithm quickly disseminates requests for help through the community.