A tuple space based agent programming framework

Software agent has become a research focus in distributed systems in recent years. This thesis aims at developing a methodology that facilitates the design and implementation of distributed agent applications. We propose an agent programming model called TSAM, which is a development framework for building distributed agent systems. TSAM provides an agent architecture that distinguishes three types of agent behaviors as (i) sensory behaviors, (ii) reactive behaviors, and (iii) proactive behaviors. Role models are used to design different proactive behaviors assigned to an agent. TSAM supports agent couplings with both message passing and distributed tuple spaces. A tuple space facilitates dynamic coordination among a group of agents that work together towards a common goal. We apply TSAM to an example of an e-market system to validate its usefulness, simplicity and support for dynamic couplings among application agents. Performance testing is conducted on the implemented system to demonstrate that the flexibility of tuple space based coordination does not incur significant runtime overhead when compared with message passing

Encrypted Shared Data Spaces

The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents’ keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given

Blackboard Rules for Coordinating Context-aware Applications in Mobile Ad Hoc Networks

Thanks to improvements in wireless communication technologies and increasing computing power in hand-held devices, mobile ad hoc networks are becoming an ever-more present reality. Coordination languages are expected to become important means in supporting this type of interaction. To this extent we argue the interest of the Bach coordination language as a middleware that can handle and react to context changes as well as cope with unpredictable physical interruptions that occur in opportunistic network connections. More concretely, our proposal is based on blackboard rules that model declaratively the actions to be taken once the blackboard content reaches a predefined state, but also that manage the engagement and disengagement of hosts and transient sharing of blackboards. The idea of reactiveness has already been introduced in previous work, but as will be appreciated by the reader, this article presents a new perspective, more focused on a declarative setting.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

Modeling Human Ad Hoc Coordination

Whether in groups of humans or groups of computer agents, collaboration is most effective between individuals who have the ability to coordinate on a joint strategy for collective action. However, in general a rational actor will only intend to coordinate if that actor believes the other group members have the same intention. This circular dependence makes rational coordination difficult in uncertain environments if communication between actors is unreliable and no prior agreements have been made. An important normative question with regard to coordination in these ad hoc settings is therefore how one can come to believe that other actors will coordinate, and with regard to systems involving humans, an important empirical question is how humans arrive at these expectations. We introduce an exact algorithm for computing the infinitely recursive hierarchy of graded beliefs required for rational coordination in uncertain environments, and we introduce a novel mechanism for multiagent coordination that uses it. Our algorithm is valid in any environment with a finite state space, and extensions to certain countably infinite state spaces are likely possible. We test our mechanism for multiagent coordination as a model for human decisions in a simple coordination game using existing experimental data. We then explore via simulations whether modeling humans in this way may improve human-agent collaboration.Comment: AAAI 201