Miguel Rebollo

invited talk by Klaus G. Troitzsch

Human social systems are among the most complex systems in our world and they share several characteristics with agents. They’re different from physical systems and living systems. He’s talking about common concepts in agency from the viewpoint of human societies and comparing them sometimes with physical systems.

Before using agents, in social sciences many approaches has been used, as econophysics/sociophysics, game theory (OGM, again, I’m becoming hate it), some simulation attempts in the 60s… ups, I’ve just discovered that our model of agreement is sociophysics: agents as particles, with vectorial additivity for their behaviours.

Other interesting thing (related with the small world model I’m trying to find) is how humans take roles. People belong to many groups at the same time and we can not classify this groups in levels, because they co-exists. 

… and many other things as communication, emergence, adaptation or trust.
socially-inspired computing

What MAS can learn from economics and social sciences

• more cooperative and secure agent societies
• create adaptative sw if valid HSS simulators can be created
• trust fromation and negotiation as design patterns for distributed systems engineering

but we’re far sway from creating socially-inspired computing systems.

At the end, too general, nothing really new and a bit boring.

This is my first ‘normal session’ in the AAMAS. Yesterday we had a very boring poster session: three hours standing up just to talk 10 mins. with 4 people :-( And today an stressing morning with 6 parallel sessions Impossible to attend the all the topics I’m interested in.

On the Significance of Synchroneity in Emergent Systems
Adam Campbell, Annie Wu

I’ve arrive late, so I’m only trying to get a chair.

On Recursive Simulation
Latek Maciej, Rob Axtell, Bogumil Kaminski

Using something calles n-th order rationality (I haven’t the foggiest idea about what it is). Oh!, it’s about rationality in games (I don’t like game theory and any utility-based solution). They have a tactical model (that represents the evolution of the environment, without decision making information from other agents). So only the ‘trajectories’ of the policies can be found, nor the policies themselves. A n-th order rationality is defined recursively and… ups, too fast… he’s in the example now :-( playing Blotto (I don’t know this game). He’s talking about cognitive capabilities but, at the end, it’s represented just by one equation. Can knowledge be reduce just to one equation?

Adaptive Learning in Complex Evolving Trade Networks
Tomas Klos, Bart Nooteboom

Motivation: task allocation in networks of trading agents, with input/aoutput relations. IN classical economics, individual nodes are optimized, whereas transaction costr economics is focus on transactions (edges). Agents are rational and opportunistic. Buyers choose make or buy something and it’s implemented using Gale-Shapley algorithm for matching (game theory again… maybe the title of this session is wrong), using preferences based on scores related with potential profit and some trust (loyalty) measure.

Some experimental results, that turn into something interesting when they begin to consider the network itself, at least the indegree and outdegree (4 max. with a random network I guess). So, they have a model to simulate organizations using agents to check hypothesis.

A Mathematical Analysis of Collective Cognitive Convergence
Van Parunak

The idea of CCC is intgeresting: how a ‘closed’ collective can ‘corrupt’ the knowledge being something ‘endemic’. And they’re using agents-based models to explain why this is happening. They have simulated that and now they have a formal model of all this stuff.

An interesting result in theorem 4: it detects when the system converges (non deseable), so it can be corrected. And this convergence depends on number of agents, the number of topics and the topic’s density.

Emergent Service Provisioning and Demand Estimation through Self-Organizing Agent Communities
Mariusz Jacyno, Seth Bullock, Michael Luck, Terry Payne

A simulation model to match supply with demand in service based communities (coalitions and teams). Very difficult to synchronise choices in a centralised way and it leads to over-provisioning of services (againt a reason to create a distributed SF federation and, why not,  using a small world model ;-) This work is based on the emergent behaviour of insect colonies (OMG, ants again!) -> limited knowledge about peers and local behaviour (it sounds to me).

One interesting idea: to change the type of a provided service  has a cost, a penalty, so the system trends to keep the services unchanged as long as possible. Besides, resources are limited so a limited-size registry of known providers are maintained by customers, whereas providers have a limited-seize registry of user’s requests.

The simulation considers the amount of memory and only two types of services are available. When you have too few or too much memory the performance is worse that in a medium case, where you know enough providers/customers to work locally without service changes.

Effective Tag Mechanisms for Evolving Cooperation
Matthew Matlock, Sandip Sen

The last one, about considering expertise in a agent network using tag mechanism. Tags are a useful mechanism to promote collaborative behavior and it allows to reuse knowledge

This is my first ‘normal session’ in the AAMAS. Yesterday we had a very boring poster session: three hours standing up just to talk 10 mins. with 4 people :-( And today an stressing morning with 6 parallel sessions Impossible to attend the all the topics I’m interested in.

On the Significance of Synchroneity in Emergent Systems
Adam Campbell, Annie Wu

I’ve arrive late, so I’m only trying to get a chair.

On Recursive Simulation
Latek Maciej, Rob Axtell, Bogumil Kaminski

Using something calles n-th order rationality (I haven’t the foggiest idea about what it is). Oh!, it’s about rationality in games (I don’t like game theory and any utility-based solution). They have a tactical model (that represents the evolution of the environment, without decision making information from other agents). So only the ‘trajectories’ of the policies can be found, nor the policies themselves. A n-th order rationality is defined recursively and… ups, too fast… he’s in the example now :-( playing Blotto (I don’t know this game). He’s talking about cognitive capabilities but, at the end, it’s represented just by one equation. Can knowledge be reduce just to one equation?

Adaptive Learning in Complex Evolving Trade Networks
Tomas Klos, Bart Nooteboom

Motivation: task allocation in networks of trading agents, with input/aoutput relations. IN classical economics, individual nodes are optimized, whereas transaction costr economics is focus on transactions (edges). Agents are rational and opportunistic. Buyers choose make or buy something and it’s implemented using Gale-Shapley algorithm for matching (game theory again… maybe the title of this session is wrong), using preferences based on scores related with potential profit and some trust (loyalty) measure.

Some experimental results, that turn into something interesting when they begin to consider the network itself, at least the indegree and outdegree (4 max. with a random network I guess). So, they have a model to simulate organizations using agents to check hypothesis.

A Mathematical Analysis of Collective Cognitive Convergence
Van Parunak

The idea of CCC is intgeresting: how a ‘closed’ collective can ‘corrupt’ the knowledge being something ‘endemic’. And they’re using agents-based models to explain why this is happening. They have simulated that and now they have a formal model of all this stuff.

An interesting result in theorem 4: it detects when the system converges (non deseable), so it can be corrected. And this convergence depends on number of agents, the number of topics and the topic’s density.

Emergent Service Provisioning and Demand Estimation through Self-Organizing Agent Communities
Mariusz Jacyno, Seth Bullock, Michael Luck, Terry Payne

A simulation model to match supply with demand in service based communities (coalitions and teams). Very difficult to synchronise choices in a centralised way and it leads to over-provisioning of services (againt a reason to create a distributed SF federation and, why not,  using a small world model ;-) This work is based on the emergent behaviour of insect colonies (OMG, ants again!) -> limited knowledge about peers and local behaviour (it sounds to me).

One interesting idea: to change the type of a provided service  has a cost, a penalty, so the system trends to keep the services unchanged as long as possible. Besides, resources are limited so a limited-size registry of known providers are maintained by customers, whereas providers have a limited-seize registry of user’s requests.

The simulation considers the amount of memory and only two types of services are available. When you have too few or too much memory the performance is worse that in a medium case, where you know enough providers/customers to work locally without service changes.

Effective Tag Mechanisms for Evolving Cooperation
Matthew Matlock, Sandip Sen

The last one, about considering expertise in a agent network using tag mechanism. Tags are a useful mechanism to promote collaborative behavior and it allows to reuse knowledge (game theory again). They introduce a boolean function to tag matching and examines four models to extend the tags.

• matched:
• pay off:
• paired reproduction. solves both problems, but they need more research to check if it is robust enough.

(check the paper to complete)

Es el título de mi póster en el AAMAS ’09. Se trata de evaluar si es válido un modelo de red de tipo small world para distribuir a un grupo de plataformas  de agentes en una red de forma que se pueda localizar fácilmente dónde se encuentra un agente con el que nos queremos comunicar.

El modelo de red que se emplea ha sido propuesto por Kleinberg y garantiza que se pouede realizar un proceso de búsqueda voraz (tomando decisiones de forma local y sin volver atrás) acotado. A este tipo de redes se les llama redes navegables.

En un artículo más extenso lo he comparado con otros modelos de redes de tipo small world y la verdad es que sale bastante bien parado: es una red tan buena como la mejor (el modelo de Barabasi según mis pruebas) en cuanto a tolerancia a fallos (destrucción de enlaces en la red), pero mucho mejor en cuanto a la búsqueda, mejorando incluso a los modelos P2P.

Referencia

REBOLLO, M.: Small World Model for Agent Search (Short Paper).- In Proc. of 8th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2009), Decker, Sichman, Sierra and Castelfranchi (eds.), May, 10–15, 2009, Budapest, Hungarytions.

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

From Agents to Artifacts Back and Forth
In MAS, environment is considered as a monolithic and centralised component. This paper proposes a model based on artifacts. An artifact has (i) an user interface that provide operations for using it, (ii) the observable state, (iii) a mechanism to signal to external artifacts and (iv) a link interface to link to other artifacts.

But artifacts are not agents, they only react, they’re passive. And they are not objects either. A sample is shown in Cartago architcture. From the agent viewpoint, artifacts embedded operational and epistemic functions.

Towards Agent-Oriented Model Driven Engineering
To create MAS is a complex activity and many methodologies integrate MDE principles. MDE is based in the concept of model. They’re talking abut how differente methodologies, such as Ingenias or Adelfe are using MDE concepts. Some considerations: (i) concepts are still evolving, (ii) own semantic concepts, (iii) a wide range of levels of abstraction. They propose Model transformation By Example (MTBE), creating automatic transformation between pairs of models and shows some examples about how it works. The idea is to provide the tools with pairs of models that correspond to a transformation, so the systmen could learn from the and apply it to other cases. An very intersenting open issue-future work is how to include negative examples.

Reducing Communication Cost Via Overhearing
Showing how to reduce the communnoication cost by using mediators that filter invalid illocutions. The cost depends on the bandwith of the communication channel and the ammount of CPU (processing time) used to detect invalid illocutions. Interesting… and some ideas that I can use for SF distribution.

Towards Organizational Agent-Oriented Operating Systems
(Confirmado… Pixel sabe leer :-) Agent are complex systems but agents and even their platforms have no help from the operative system (OS), so they (we) are trying to define-and meybe to create-an OS that incorporate more complex abstractions to facilitate the execution of the agents.

Instead of being the process the basic exectional entity, agents organisations are included into the OS. Its based on a client-server view (I don’t like it), where there’re agents that provide services and others than ask from them. Services can be classified into two types: operations and resources. Operation serv. are sw services executed by an agent (open) and Resource serv. are hw services provided by devices.

What’s the difference between this proposal and middleware? I guess that it complicates a lot the OS design without giving clear advantages. I think that is better to provide basic management for agent concepts (as communication, roles, norms, organisations and so on), but we don’t need to have agents inside the operative systems.

Tags: agent, developtment, mdd, mda, communication, cartago, ingenias, adelfe

Programming Social Processes with Action Languages
A social process is a joint of activities (business, poitical, administrative and so on) performed in a social context. It can be a computational society when a :SocialMiddleware is provided and it can be programmed as a first-class social connector (:SocialInteraction). The abstract machine for the SOcialMiddleware they use action languages (C+): a declarative language to specify structure and dynamics, based upon a propositional, non-monotonic, causal logic, and Ccalc tool (SAT solver).

The social middleware is defined through a set of sorts, objects, fluents, actions, variables and axioms. But to reduce the complexity of these specifications they make a sort-oriented specification. He explains using a tennis match example how the society can be modelled.

WIth all that, a programming language for agent societies can be defined (SPEECH: a societal programming language – www.speechlang.org).

Representing and Reasoning about Norm-Governed Organisations with Semantic Web Languages
SW languages are more limited, but they offer a stardard language (open), advantadges in reasoning (decidability and optimized reasoners). They want to capture roles and role classification, institutionalised powers, normative systems, violations and temporal relationships (hey…. just as I want!!! I have to read it carefully). OWL and SWRL extended for temporal relations (SWRLTab editor) for before, after and during (–> converted into PDDL).

They define permissions, abbligations and permision for roles and inheritance of norms. You can override them if you need more especific norms. There’re general rules form norms (ex. if an act is permitted then it’s not prohibited / if an act is obligatory the it’s permitted… ) Other cocept modelled is “power” (a role has the powerto execute an action). Norms can have conditions and deadlines, but the DL reasoner has to be extended to del with temporal relationships (this can be an interesting work to do) To detect violations, the system can check if an agent triesto perform an act that is prohibited. That can be detected automatically by the reasoner.

But we can reason an inconsistent ontology by tolerating contradictions (that’s interesting for open systems or self-organising systems)

Limitations (comparing with event calc.): only binary operators, static knowledge, no modifications

On Partial Deductions and Conversational Agents
Many times, human conversations include more information that a simple yes/no answer, so if agents want to interact with human complex conversation schemes have to be included in their mental state.

The mental state of an agent is formed by a ….., a …. and a set of rules. Goals are facts that agents want to be solve. THe input and the output interface are set of facts. Agents communicate using an own simple speech act messages. Interface engine os based on rle specialisation uses an approximate reasoning context and the true value is not binary, but a fuzzy one.

Examples to show the mentak state cycle and hoe agents communicates to complete their information.

Tags: eumas, programming, reasoning, semantic web, owl, swrl, swrltab

Coallition Structure Generation: Dynamic Programming Meets Anytime Optimization
Just how to optimize coallition formation based on its utility. Nothing new, but the method used: an anytime algorithm (IP). He’s comparing with a previos work based on dynamic programming (IDP). The proposal is to divide the search space in subspaces and to add an upper and a lower bound. The subspaces are made by the number of agents in eachs group (f.i. [1,3] means all coallitions formed by one isolated agent and a group of 3). He adjust the behaviour of the algorithm between being IP or IDP. Good results…. but for 23 agents only!! Let’s try with 100. This solution is O(n^n).

Only a question: they’ve published a paper (about IDP)  with worse results than a previous one (IP) And they’re only comparing with themselves. I can’t do that, reviwers don’t allow me to do that.

Optimal Coalition Structure Generation In Partition Function Games
A question: what happen if the value of a coallition depends on the value of the rest of the coallitions? (that is: the partition function). There’re many example of real systems working in that way; economics (petrol, R&D coallitions or coordination of monjetary policies) and other areas.

Patterns:

• positive externalities: when one coallition is formed all the rest increase their value
• nevative externalities: when one coalition is formed all the rest decrease its value
• super-additive: when one coallition is formed it increases its value
• sub-additive: when one coallition is formed it decreases its value

and he consideres its combinations. He explains the algorithms used to create the coallitions, usgin the same algorithm that in the previous speech (anytime).

A problem with all that: how the utility is calculated for coallitions? I have no faith in utility.

From Agent Games Protocols to Implementable Roles
Problems:service composition at run-time. He shows an example about merchant delivery, and shows that protocols can content errors, that can be solve by taking into account roles to deal with invisible transitions. Ups, that’s the end and I haven’t the point :-( I have no idea what he is talking about.

Adaptation in a P2P Scenario with 2-LAMA
Jordi explains that MAS organization can be adapted by using a layer of specialised agents in charge of supervise the systen. Itis applied in a P2P environment. The organisation is formed by a set of roles, protocols and norms. Agents are organised in two levels: Domain-level (DL) and Meta-level (ML).

Tos test it, they’ve used a modified (simplifies) version of BitTorrent protocol. Domain-level agents are organised in clusters and each cluster is supervised by an assistant in a Meta-level. Experiments have been organised in 3 arqchitectures: All4all, centralised and distributed. Good enogh results.

What’s the difference with P4P? I’ll look for it.

Tags: eumas.coallition, coordination