AGENT TECHNOLOGY ROADMAP
3 The Broad Agent Roadmap
3.1 Predictions
In any high-technology domain, the systems deployed in commercial or industrial applications tend to embody research findings somewhat behind the leading edge of academic research. Multi-agent systems are no exception to this, with currently-deployed systems having features found in published academic research and prototypes of three to five years ago. By looking at current academic research interests and areas of focus, we are able to extrapolate future trends in deployed systems.
Accordingly, we have identified four broad phases of the future development of deployed multi-agent systems. These phases are, of necessity, only indicative, since some companies and organisations will be leading users of agent technologies, pushing applications ahead of these phases, while many others will be laggards. We aim to describe the majority of deployed applications at each time period. Note that this view on timescales takes the development view rather than the research view in that typically research is about three to five years ahead of development in this context. At the same time, the predictions are bold, and relate to the beginning of development rather than full and successful take-up. The time phases are distinguished along five dimensions:
- The degree to which the participating agents share common domain knowledge and common goals.
- The degree to which participating agents are designed by the same or diverse design teams.
- The nature of the communications languages and interaction protocols used by the agents participating in the multi-agent systems. This can range from ad hoc languages through fixed standardised languages, to emergent languages.
- The scale of the system, e.g., how many agent participants can be supported by the system, how many users, or the complexity of the system as a whole.
- The design methodologies (if any) used for the design of the system. For example, while there are currently established object-oriented development methodologies, no such routes exist for agent-oriented systems, which must either use unsuitable or ad hoc methods.
3.2 Phase 1: Current (c. 2000-2002)
Multi-agent systems in current deployment are typically designed by one design team for one corporate environment, with participating agents sharing common high-level goals in a single domain. These systems may be characterised as closed. The communications languages and interaction protocols are typically in-house protocols, and are defined by the design team prior to any agent interactions. Systems are usually only scalable under controlled, or simulated, conditions (though efforts are underway to ensure to address this, and Tryllian's agent platform, for example, can run many tens of thousands of active agents). Design approaches tend to be ad hoc, inspired by the agent paradigm rather than using any specific methodologies. Examples of the systems developed in this phase are those for the management of utility networks.
It is likely that, for the foreseeable future, there will be a substantial commercial demand for closed multi-agent systems because of the security concerns that arise from open systems. While progress in this respect will change the nature of agent systems, the importance of closed, well protected systems must not be underestimated.
3.3 Phase 2: Near-Term Future (c. 2003-2005)
In the next phase of development, systems will increasingly be designed to cross corporate boundaries, so that the participating agents have fewer goals in common, although their interactions will still concern a common domain. However, despite this diversity, all participating agents are designed by the same team designing the system and will share common domain knowledge. Increasingly, standard agent communications languages, such as FIPA ACL, are used, but interaction protocols remain non-standard. These systems are able to handle large numbers of agents in pre-determined environments, such as those of Grid applications and Agentcities. Development of these systems will increasingly use top-down methodologies, such as GAIA, or middle-out methodologies supporting applications based on service-oriented architectures. Example systems developed in this phase include those to enable automated scheduling coordination between different departments of the same company, closed-user groups of manufacturing suppliers engaged in electronic procurement activities, or network-centric operations.
3.4 Phase 3: Medium-Term Future (c. 2006-2008)
In the third phase, multi-agent systems will permit participation by heterogeneous agents, designed by different designers or teams. Any agent will be able to participate in these systems, provided their (observable) behaviour conforms to publicly-stated requirements and standards. However, these open systems will typically be specific to particular application domains, such as B2B eCommerce or Bioinformatics. The languages and protocols used in these systems will be agreed and standardised, perhaps being drawn from public libraries of alternative protocols. These libraries will likely differ by domain. Ontologies, in particular, will be important to master this semantic heterogeneity.
The systems will scale to large numbers of participants, although typically only within the domains concerned. The third phase will see the development of bridge agents, able to translate between separate domains. Thus, for example, a multi-agent system for automated meta-analysis of research results in some area of biology will be able to utilise bridge agents to undertake commercial negotiations when interaction with an eCommerce system is required, say for access to information protected by patent. In the third phase, system development will proceed by standard agent-specific design methodologies, including templates and patterns for different types of agents and types of agent systems. Semantic issues related to e.g., coordination between heterogeneous agents and access control, are of particular importance here.
Examples of systems in this phase will be corporate B2B electronic procurement systems permitting participation by any supplier, rather than closed user groups.
3.5 Phase 4: Long-term Future (c. 2009-onwards)
The fourth phase in this projected future will see the development of open multi-agent systems spanning multiple application domains, and involving heterogeneous participants developed by diverse design teams. Agents seeking to participate in these systems will be able to learn the appropriate behaviour for participation in the course of doing so, rather than having to prove adherence before entry. Although standard communications languages and interaction protocols will have been available for some time, systems in this phase will enable these to emerge by evolutionary means from actual participant interactions, rather than being imposed. Of course, such languages, protocols and behaviours may be mere refinements of previously-developed standards, but will be tailored to their particular contexts of use.
By this phase, systems will be fully scalable in the sense that they will not be restricted to arbitrary limits (on agents, users, complexity, etc). As with the previous phase, systems development will proceed by use of rigorous agent-specific design methodologies. Multi-agent systems deployed in this phase, for example, will support fully ambient computing.
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