Decision Making Intelligent Agent on SOX Compliance over the Imports Process

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility  of the Imports Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques measuring at the same time the quality of how things were done on this specific process of the analyzed business case. SOX Law in effect nowadays is worldwide facto standard for financial and economical operations of private sector with the main objective to protect investors of private sector and promote the financial health of private companies. In this framework we have developed a decision support intelligent expert model to help SOX control bodies, companies and auditors to support their SOX compliance decisions based on well founded bases like Artificial Intelligence and Theory of Argumentation. The model here presented incorporates several key concepts like pre-existing expert knowledge base, a formalized and structure way to evaluate an existing business case focusing on the Imports Process, a semi automated fuzzy dynamic knowledge learning protocol and an structure method to evolve based on the facts of the business case and suggest an specific decision about the SOX compatibility of the specific business case. Keywords: Multiagent Systems (MAS), Expert Systems (ES), Business Intelligence (BI), Decision Support Systems (DSS), Sarbanes-Oxley Act (SOX), Argumentation, Artificial Intelligence

Decision Making Intelligent Agent on SOX Compliance over the Goods Receipt Processs

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility  of the Goods Receipt Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques measuring at the same time the quality of how things were done on this specific process of the analyzed business case. SOX Law in effect nowadays is worldwide facto standard for financial and economical operations of private sector with the main objective to protect investors of private sector and promote the financial health of private companies. In this framework we have developed a decision support intelligent expert model to help SOX control bodies, companies and auditors to support their SOX compliance decisions based on well founded bases like Artificial Intelligence and Theory of Argumentation. The model here presented incorporates several key concepts like pre-existing expert knowledge base, a formalized and structure way to evaluate an existing business case focusing on the Goods Receipt Process, a semi automated fuzzy dynamic knowledge learning protocol and an structure method to evolve based on the facts of the business case and suggest an specific decision about the SOX compatibility of the specific business case. Keywords: Multiagent Systems (MAS), Expert Systems (ES), Business Intelligence (BI), Decision Support Systems (DSS), Sarbanes-Oxley Act (SOX), Argumentation, Artificial Intelligence

On the effect of dynamic environments in defeasible reasoning

The design of intelligent agents has become a key issue for many interesting applications. Given that there is no universally accepted definition of intelligence, Russell developed the notion of rational agency as an alternative for the characterization of intelligent agency [11]. In short, an agent is said to be rational if it performs the right actions according to the information it possesses and the goals it wants to achieve.Eje: Inteligencia Artificial Distribuida, Aspectos Teóricos de la Inteligencia Artificial y Teoría de la ComputaciónRed de Universidades con Carreras en Informática (RedUNCI

Distributed knowledge bases : A proposal for argumentation-based semantics with cooperation

O objectivo principal desta dissertação é definir um ambiente de negociação, baseada em argumentação, para bases de conhecimento distribuídas. As bases de conhecimentos são modeladas sobre um ambiente multiagente tal que cada agente possui uma base de conhecimento própria. As bases de conhecimento dos diversos agentes podem ser independentes ou podem incluir conhecimentos comuns. O requisito mínimo para haver negociação num ambiente multiagente é que os agentes tenham a capacidade de fazer propostas, que poderão ser aceites ou rejeitadas. Numa abordagem mais sofisticada, os agentes poderão responder com contra-propostas, com o intuito de alterar aspectos insatisfatórios da pro­ posta original. Um tipo ainda mais elaborado de negociação será o baseado em argumentação. A metáfora da argumentação parece ser adequada à modelação de situações em que os diferentes agentes interagem com o propósito de determinar o significado das crenças comuns. Numa negociação baseada em argumentação, as (contra­) propostas de um agente podem ser acompanhadas de argumentos a favor da sua aceitação. Um agente poderá, então, ter um argumento aceitável para uma sua crença, se conseguir argumentar com sucesso contra os argumentos, dos outros agentes, que o atacam. Assim, as crenças de um agente caracterizam-se pela relação entre os argumentos "internos" que sustentam suas crenças, e os argumentos "externos" que sustentam crenças contraditórias de outros agentes. Portanto, o raciocínio argumentativo baseia-se na "estabilidade externa" dos argumentos aceitáveis do conjunto de agentes. Neste trabalho propõe-se uma negociação baseada em argumentação em que, para chegarem a um consenso quanto ao conhecimento comum, os agentes constroem argumentos que sustentam as suas crenças ou que se opõem aos argumentos dos agentes que as contradizem. Além disso, esta proposta lida com conhecimento incompleto (i.e., argumentos parciais) pela definição de um processo de cooperação que permite completar tal conhecimento. Assim, a negociação entre agentes é um processo argumentativo-cooperativo, em que se podem alternar os argumentos contra e a favor das crenças de um agente. Para a formação das suas crenças, a cada agente Ag está associado um conjunto Cooperate de agentes com quem coopera e um outro Argue de agentes contra quem argumenta. A negociação proposta permite a modelação de bases de conhecimento hierárquicas, representando, por exemplo, a estrutura de uma organização ou uma taxonomia nalgum domínio, e de ambientes multi-agente em que cada agente representa o conhecimento referente a um determinado período de tempo. Um agente também pode ser inquirido sobre a verdade de uma crença, dependendo a resposta do agente em questão e de quais os agentes que com ele cooperam e que a ele se opõem. Essa resposta será, no entanto, sempre consistente/ paraconsistente com as bases de conhecimento dos agentes envolvidos. Esta dissertação propõe semânticas (declarativa e operacional) da argumentação numa base de conhecimento de um agente. Partindo destas, propõe, também, semântica declarativa da negociação baseada em argumentação num ambiente multi-agente. ⓿⓿⓿ ABSTRACT: The main objective of this dissertation is to define an argumentation-based negotiation framework for distributed knowledge bases. Knowledge bases are modelling over a multi-agent setting such that each agent possibly has an independent or overlapping knowledge base. The minimum requirement for a multi-agent setting negotiation is that agents should be able to make proposals which can then either be accepted or rejected. A higher level of sophistication occurs when recipients do not just have the choice of accepting or rejecting proposals, but have the option of making counter offers to alter aspects of the proposal which are unsatisfactory. An even more elaborate kind of negotiation is argumentation-based. The argumentation metaphor seems to be adequate for modelling situations where different agents argue in order to determine the meaning of common beliefs. ln an argumentation-based negotiation, the agents are able to send justifications or arguments along with (counter) proposals indicating why they should be accepted. An argument for an agent's belief is acceptable if the agent can argue successfully against attacking arguments from other agents. Thus, agent's beliefs are characterized by the relation between its "internal" arguments supporting its beliefs and the "external" arguments supporting the contradictory beliefs of other agents. So, in a certain sense, argumentative reasoning is based on the "external stability" of acceptable arguments in the multi-agent setting. This dissertation proposes that agents evaluate arguments to obtain a consensus about a common knowledge by both proposing arguments or trying to build opposing arguments against them. Moreover, this proposal deals with incomplete knowledge (i.e. partial arguments) and so a cooperation process grants arguments to achieve knowledge completeness. Therefore, a negotiation of an agent's belief is seen as an argumentation-based process with cooperation; both cooperation and argumentation are seen as interlaced processes. Furthermore, each agent Ag has both set Argue of argumentative agents and set Cooperate of cooperative agents; every Ag must reach a consensus on its arguments with agents in Argue, and Ag may ask for arguments from agents in Cooperate to complete its partial arguments. The argumentation-based negotiation proposal allows the modelling a hierarchy of knowledge bases representing, for instance, a business's organization or a taxonomy of some subject, and also an MAS where each agent represents "acquired knowledge" in a different period of time. Furthermore, any agent in an MAS can be queried regarding the truth value of some belief. It depends on from which agent such a belief is inferred, and also what the specification in both Argue and Cooperate is, given the overall agents in the MAS. However, such an answer will always be consistent/paraconsistent with the agents' knowledge base involved. This dissertation proposes a (declarative and operational) argumentation semantics for an agent's knowledge base. Furthermore, it proposes a declarative argumentation-based negotiation semantics for a multi-agent setting, which uses most of the definitions from the former semantics

Software agents as legal persons

The Law has long been recognizing that, besides natural persons, other entities socially engaged must also be subject of rights and obligations. Western laws usually recognize Corporate Bodies as having legal personality and capacity for every right and obligation needed or convenient to the prosecution of its social goals. But can we foresee a similar attribution of such a regime to software agents? In other words, are intelligent software agents capable of being personified? One of the main characteristics of a personality is the existence of a physical being or organization provided with its own will. In that sense, intelligent software agents are quite close to human beings. Indeed, they have a physical existence, and they have the capability of learning and of having a will of their own

Some approaches to Belief Bases Merge

In this work, we de fine some non-prioritized merge operators, that is, operators for the consistent union of belief bases. We de ne some postulates for several kinds of merge operator and we give different constructions: trivial merge, partial meet merge and kernel merge. For some constructions we provide representation theorems linking construction with a set of postulates. Finally, we propose that the formulated operators can be used in some multi-agent systemsVII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Using logic programs to model an agent's epistemic state

The notion of rational agency was proposed by Russell [9] as an alternative characterization of intelligence agency. Loosely speaking, an agent is said to be rational if it perfomns the right actions according to the information it possesses and the goals it wants to achieve. Unfortunately, the enterprise of constructing a rational agent is a rather complex task. Although in the last few years there has been an intense flowering of interest in the subject, it is still in its early beginnings: several issues remain overlooked or addressed under too unrealistic assumptions. As slated by Pollock. [5], a rational agent should have models of itself and its surroundings, since it must be able to draw conclusions from this knowledge that compose its set of beliefs. Traditional approaches rely on multi-modal logics to represent the agent's epistemic state [7. l]. Given the expressive power of these formalisms, their use yields proper theoretical models. Nevertheless, the advantages of these specifications lend to be lost in the transition towards practical systems: there is a tenuous relation between the implementations based on these logics and their theoretical foundations [8]. Modal logics systems suffer from a number of drawbacks, notably the well-known logical omniscience problem [10]. This problem arises as a by-product of the necessitation rule and the K axiom, present in any normal modal system. Together, these ruIes imply two unrealistic conditions: an agent using this system must know all the valid formulas, and its beliefs should be closed under logical consecuence. These properties are overstrong for a resource-bounded reasoner lo achieve them. Therefore, the traaditional modal logic approach is not suitable for representing practical believers [11]. We intend to use logic programs as an alternative representation for the agent's epistemic state. This formalization avoids the aforementioned problems of modal logics, and admits a seamless transition between theory and practice. In the next section we detail our model and highlight its advantages. Next, sectiol1 3 prescnts sume conclusions and reports on the forthcoming work.Eje: Aspectos teóricos de inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

Multi-Agent Systems for Dynamic Forensic Investigation

In recent years Multi-Agent Systems have proven to be a useful paradigm for areas where inconsistency and uncertainty are the norm. Network security environments suffer from these problems and could benefit from a Multi-Agent model for dynamic forensic investigations. Building upon previous solutions that lack the necessary levels of scalability and autonomy, we present a decentralised model for collecting and analysing network security data to attain higher levels of accuracy and efficiency. The main contributions of the paper are: (i) a Multi-Agent model for the dynamic organisation of agents participating in forensic investigations; (ii) an agent architecture endowed with mechanisms for collecting and analysing network data; (iii) a protocol for allowing agents to coordinate and make collective decisions on the maliciousness of suspicious activity; and (iv) a simulator tool to test the proposed decentralised model, agents and communication protocol under a wide range of circumstances and scenarios