Fluorescent anion sensors based on 4-amino-1,8-naphthalimide that employ the 4-amino N-H

The new charge neutral 4-amino-1,8-naphthalimide based anion sensors 2 and 3 bind to both acetate and dihydrogenphosphate with 1:1 stoichiometry through hydrogen bonding to both thiourea N–H atoms and in the case of dihydrogenphosphate, the naphthalimide 4 amino N–H group as well. This was clearly established from ¹H NMR titration experiments with H₂PO₄^- in DMSO-d₆ where a substantial shift in the resonance for the naphthalimide N–H was observed concomitant with the expected migration of the thiourea N–H chemical shifts. The binding constants determined from the titration studies indicate that the new sensors bind H₂PO₄^- more strongly than AcO⁻. Fluorescence titrations with sensor 3 indicate quenching of 59% and 36% upon addition of acetate and dihydrogenphosphate, respectively.

Interaction among agents that plan

The development of practical agent languages has progressed significantly over recent years, but this has largely been independent of distinct developments in aspects of multiagent cooperation and planning. For example, while the popular AgentSpeak(L) has had various extensions and improvements proposed, it still essentially a single-agent language. In response, in this paper, we describe a simple, yet effective, technique for multiagent planning that enables an agent to take advantage of cooperating agents in a society. In particular, we build on a technique that enables new plans to be added to a plan library through the invocation of an external planning component, and extend it to include the construction of plans involving the chaining of subplans of others. Our mechanism makes use of plan patterns that insulate the planning process from the resulting distributed aspects of plan execution through local proxy plans that encode information about the preconditions and effects of the external plans provided by agents willing to cooperate. In this way, we allow an agent to discover new ways of achieving its goals through local planning and the delegation of tasks for execution by others, allowing it to overcome individual limitations.

Norm-based behaviour modification in BDI agents

While there has been much work on developing frameworks and models of norms and normative systems, consideration of the impact of norms on the practical reasoning of agents has attracted less attention. The problem is that traditional agent architectures and their associated languages provide no mechanism to adapt an agent at runtime to norms constraining their behaviour. This is important because if BDI-type agents are to operate in open environments, they need to adapt to changes in the norms that regulate such environments. In response, in this paper we provide a technique to extend BDI agent languages, by enabling them to enact behaviour modification at runtime in response to newly accepted norms. Our solution consists of creating new plans to comply with obligations and suppressing the execution of existing plans that violate prohibitions. We demonstrate the viability of our approach through an implementation of our solution in the AgentSpeak(L) language.

Evolutionary Testing of Autonomous Software Agents

A system built in terms of autonomous agents may require even greater correctness assurance than one which is merely reacting to the immediate control of its users. Agents make substantial decisions for themselves, so thorough testing is an important consideration. However, autonomy also makes testing harder; by their nature, autonomous agents may react in different ways to the same inputs over time, because, for instance they have changeable goals and knowledge. For this reason, we argue that testing of autonomous agents requires a procedure that caters for a wide range of test case contexts, and that can search for the most demanding of these test cases, even when they are not apparent to the agents’ developers. In this paper, we address this problem, introducing and evaluating an approach to testing autonomous agents that uses evolutionary optimization to generate demanding test cases.

Initial value generation for matchmaking in middle agents

One of the major challenges that agents used in open environments must face is that they must be able to find each other. This is because in an open environment, agents might appear and disappear unpredictably. To address this issue, middle agents have been proposed. The performance of middle agents relies heavily on the matchmaking algorithms used. Matchmaking is the process of finding an appropriate provider for a requester through a middle agent. The practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. Thus the track records of agents in accomplishing similar tasks in the past should be taken into account in matchmaking process. Considering that there are no track records available at the launching of an agent system, this paper discusses some ways to provide reasonable initial values for the track  records. With the agents' history and the initial vallies ofthe track records, the performance of matchmaking algorithms can be improved significantly.

An improvement to matchmaking algorithms for middle agents

A question frequently asked in multi-agent systems (MASs) concerns the efficient search for suitable agents to solve a specific problem. To answer this question, different types of middle agents are usually employed. The performance of middle agents relies heavily on the matchmaking algorithms used. Matchmaking is the process of finding an appropriate provider for a requester through a middle agent. There has been substantial work on matchmaking in different kinds of middle agents. To our knowledge, almost all currently used matchmaking algorithms missed one point when doing matchmaking -- the matchmaking is only based on the advertised capabilities of provider agents. The actual performance of provider agents in accomplishing delegated tasks is not considered at all. This results in the inaccuracy of the matchmaking outcomes as well as the random selection of provider agents with the same advertised capabilities. The quality of service of different service provider agents varies from one agent to another even though they claimed they have the same capabilities. To this end, it is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. An improvement to matchmaking algorithms is proposed, which makes the algorithms have the ability to consider the track records of agents in accomplishing delegated tasks. How to represent, accumulate, and use track records as well as how to give initial values for track records in the algorithm are discussed. A prototype is also built to verify the algorithm. Based on the improved algorithm, the matchmaking outcomes are more accurate and reasonable.