Mes: diciembre 2008

Enforcing Security in the AgentScape Middleware
AgentScape is a middlewareto create agent-based applications and in this paper they’re showing how threads can be managed by using the security architecture for AgentScape. He begins with the architecture (see in AgentScape web wite).Two basic problemas: malicious hosts and malicious agents. SO basic sec. requirements are (i) authentification, (ii) integrity-migration- and (iii) authorisation.

Developing Intelligent Agents in Android Platform
Well, this is mine, so I’ll write it later :-)

Magentix: a Multiagent Platform Integrated in Linux
I know that, so I haven’t a lot of things to say. Magentix is an agent platform that are focus en scalability and efficiency, so it is quite integrated with the operative systems instead of using middleware (what will get him into trouble in a moment ;-). AMS (white pages) and DF (yellow pages) are distributed in different hosts and all that information is replicated (I hate that). Something interesting is how organisations are managed by the platform by the Organisational Unit Manager (OUM).

Only a question… what’s new on that? It sounds to me a lot!

From the assistants: about the RDF codification of messages (performance); problems: interoperability, integration with other tools, and AN ENVIRONMENT FOR PROGRAMMING DIFFERENT THAT VI!!!! ; other about scalability with AMS distribution in large systems (I said it!). And the last one, why comparing only with JADE.

Tags: eumas, agent, tools, agentspace., magentix, android, mda, mdd, pim, psm, jade-leap

An Agent Based System for Distributed Information Management: A Case Study
Sorry, I’m late :-(

Scholar Agent Alpha
Auction mechanism for authors (they pay for having their paper published). WHen they win the auction then they can use their «rights» to publish the paper. They are using a vickery auction (second price, closed envelope). the process is the following

1. call for papers
2. authors register themselves
3. authors bids (once)
4. system reports to winners and loser
5. wining paper is submitted for publication (and paid)

More cycles can be done, so agents can modify their bids and try to win.

Conservative Re-Use Ensuring Matches for Service Selection
Automatic retrieval, a semantic is needed (OWL-S, WSMO) and IOPEs has to be annotated. And flexible matches are very important (services that do not exactly match). But current semantic matchmaking considers services as a single operation. She proposes for the services to have roles inside a composed service. But for many of the operations are offered by patterns that are still unkown. And context usually is not taken into account, so the global goal can not be preserved, so they define an action-based representation of the operations of a service and an extension of re-use ensuring matches to produce substitutions that preserve goals. A modal logic is used; states are fluents and there’re 4 types of operations: one-way, notification, request-response and solicit-response. With those elements, choreography is defined through roles and all complex services will still works if conservative substitution is guaranteed. ANd this can be done if casual chains of actions are not broken when actions are sbustituted. What is important is that the problem of determining if a substitution is conservative is decidible.

A big «but»: youi need to have a choreography. Services can not discover service compositions, but working over a composite service and look for suitable substitutions.

Evolving Ontological Knowledge Bases through Agent Collaboration
Problem: an agent gives a queary about a concept c that it is not known, so the question can not be answered. Option 1: consult a mediator. Option 2: consult other agents. After that, some fragment of the ontology can be requested so the original agent can augment its knowledge and perform better interactions. But it has a cost and may not benefit the agent (it do not weigh the cost) ==> evolutionary method to augment ontologies with concepts related to its intereset domain. Two steps:

1. Merge Fragments: check which ones are related and merge them into one, create a powerset of all the axioms and, for each memmber of the powerset, check the consistence with existing ontology
2. Selection Process: find the average depth of the fragment, select the related properties level by level and incorporate them to the ontology.

This has been checked with an small number of agents (5 query and 10 speciliased) and several benchmarks. But htere’s no method for measuring the complexity of a T-Box.

Very interesting. One of the best papers I’ve seen these days.

Tags: eumas, agents, information, services, ontologies, owl-s, iope

Norms for Agent Service Controlling
About how add a normative system in an open system where agents and web services co-exist and interact. Agents are grouped in organisational units (OU), as coallitions or teams. OU provides services to the agents (or even the designers) to manage the organisation. They’re classified into 3 types: structrural (norm, role and unit creation), informational (about the current state) and dynamic (role adquisition).

Norms regulate the organisation and they’re divided into organisational and functional norms. She shows with an example the different type of norms, services and how all that works.

One thing that I don’t like is the definition of a new language. There’s well known logic specification and standards to formalise these concepts. A new language nowadays just complicate the interaction, even more for open systems…. and Pablo Noriega thinks as me :-)

Towards the Group FormationRecognition through Social Norms
Social norms are a good complement to laws, based on coordinated reaction on the members of the group. A norm is a set of observables and one action. How agent recognise as members of the same group? (that is, they have the same set of rules) They follow 4 algorithms: (i) basic (interact and save) (ii) the friends of my friends are also my friends (whitelist), (iii) blacklist (the opposite one) and (iv) labelling. Labels are put on the agents when they interact. They’re public: all agents can see them, but one agent can remove its own labels. False positives behave similar in the case of white and black lists. And it works better (obviously) for heterogeneous groups than for homogeneous groups. Very interesting. Take a closer look to that.

Integrating Image and Reputation Information in BDI Agents
3 approaches to control interactions among agents are possible: security, institutional and social (reputatin based). The last one can be modelled in a centralised way (as eBay) or decentrlised way (more interesting) and he’s going to present the Repage system to model image and reputation, integrated into a BDI agent. The difference between them is that image is my own view of the agent (experience-based), whereas reputation is what other agents say. A recommended lecture: the paper with six definitions for trust (look for it)

An Extendedc. Using Institutions To Foster Compliance in Open Multi-Agent Systems
Problem in open systems: heterogenous agents, with conflicting individual goals and limited trust. Some uncertainties (parametric -> environmental) can’t be reduced, but strategic ones can (decide if one agent has a bad behaviuour deliverately). In the case of anoinymous communities with esporadic interaction, it is very difficult to get efficient exchanges in the long run. But this can be solve even without superior detection capabilities by extending it. Well, she’s changing a bit the game because she adds a new player, but it is no serious.

Tags: eumas, agents, services, norms, organisation, institution