An agent programming manifesto

There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are confined to a small number of niche areas, and adoption of agent programming languages in mainstream software development remains limited. This state of affairs is widely acknowledged within the community, and a number of reasons and remedies have been proposed. In this paper, I present an analysis of why agent programming has failed to make an impact that is rooted in the class of programming problems agent programming sets out to solve, namely the realisation of flexible intelligent behaviour in dynamic and unpredictable environments. Based on this analysis, I outline some suggestions for the future direction of agent programming, and some principles that I believe any successful future direction must follow

MsATL: a Tool for SAT-Based ATL Satisfiability Checking

We present MsATL: the first tool for deciding the satisfiability of Alternating-time Temporal Logic (ATL) with imperfect information. MsATL combines SAT Modulo Monotonic Theories solvers with existing ATL model checkers: MCMAS and STV. The tool can deal with various semantics of ATL, including perfect and imperfect information, and can handle additional practical requirements. MsATL can be applied for synthesis of games that conform to a given specification, with the synthesised game often being minimal

Future directions in agent programming

Agent programming is a subfield of Artificial Intelligence concerned with the development of intelligent autonomous systems that combine multiple capabilities, e.g., sensing, deliberation, problem-solving and action, in a single system. There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are currently confined to a small number of niche areas, and adoption of agent programming languages (APLs) in mainstream software development remains limited. In this paper, I argue that increased adoption of agent programming is contingent on being able to solve a larger class of AI problems with significantly less developer effort than is currently the case, and briefly sketch one possible approach to expanding the set of AI problems that can be addressed by APLs. Critically, the approach I propose requires minimal developer effort and expertise, and relies instead on expanding the basic capabilities of the language

An agent programming manifesto

There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are confined to a small number of niche areas, and adoption of agent programming languages in mainstream software development remains limited. This state of affairs is widely acknowledged within the community, and a number of reasons and remedies have been proposed. In this paper, I present an analysis of why agent programming has failed to make an impact that is rooted in the class of programming problems agent programming sets out to solve, namely the realisation of flexible intelligent behaviour in dynamic and unpredictable environments. Based on this analysis, I outline some suggestions for the future direction of agent programming, and some principles that I believe any successful future direction must follow

Exploring the resource recovery potentials of municipal solid waste: a review of solid wastes composting in developing countries

Population explosion, high urbanization and improved living standards have induced rapid changes in quantities and materiacompositions of solid waste generation globally. Until recently solid waste disposal in landfills and open dump sites waconsidered more economical and it is the most widely used methods in developing countries. Hence the potentials in the othealternative methods such as the resource recovery and recycling and their integration into waste management have been scarcelassessed. However, the ever growing challenges posed by the rapidly increasing quantities and compositions of solid wastes ideveloping countries led to the searching for alternative waste disposal methods. In this regard the paper presented an assessmenof the resource potentials of municipal solid waste materials arising from cities in developing countries as a strategy fosustainable solid waste management. Using published data on solid waste composition the paper has identified that there is higpotentials of composting in the solid waste stream from cities in developing countries. In conclusion, it recommended the recoverof organic waste material and papers for composting and the recycling of plastic, metals, textiles and others to explore their resource recovery potentials. This will largely reduce the ultimate quantities of solid waste for disposal and lower the operatincosts. This strategy will achieve sustainable waste management in developing countries. It is hoped that the paper has provided useful guide for wastes management policy decisions in developing countries