Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

Computational Complexity of Strong Admissibility for Abstract Dialectical Frameworks

Abstract dialectical frameworks (ADFs) have been introduced as a formalism for modeling and evaluating argumentation allowing general logical satisfaction conditions. Different criteria used to settle the acceptance of arguments arecalled semantics. Semantics of ADFs have so far mainly been defined based on the concept of admissibility. Recently, the notion of strong admissibility has been introduced for ADFs. In the current work we study the computational complexityof the following reasoning tasks under strong admissibility semantics. We address 1. the credulous/skeptical decision problem; 2. the verification problem; 3. the strong justification problem; and 4. the problem of finding a smallest witness of strong justification of a queried argument

Belief systems for persuasive discourse planning

This thesis is concerned with the problem of construction of the logical structure of a persuasive discourse. A persuasive discourse can be defined as a monodirectional form of communication, generated by a speaker in order to convince a hearer about the validity (or fallacy) of a specific belief The construction of the structure of a persuasive discourse is realized, in this work, through the adoption of two basic elements: a belief system and a planning system. The planning system is used as a tool for the automatic generation of the discourse structure (or plan), obtained through the decomposition of the assigned (communicative) goals of persuasion, aimed at producing specific effects on the hearer’s beliefs. The belief system is adopted in order to endow the planning process with a formal language of beliefs for the representation of such goals, and with the mechanisms which govern the propagation of their (expected) effects on the rest of the hearer's belief state. The main results presented consist of the formalization of a paradigm for specification of belief systems, and of a method — whose correctness is formally proved — for their integration with planning systems. The formalization of a belief system for discourse structure representation (defined in accordance with the theoretical paradigm) is also given, together with the description of its implementation and integration with a specific planner, which resulted in the actual completion of a system for the automatic generation of persuasive discourse plans

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B