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The purpose of this paper is to explore the extent to which formal logic can be applied to conflict analysis and resolution. It is motivated by the idea that conflicts can be understood as inconsistent sets of interests.

A simple propositional model, based on propositional logic, which can be used to analyze conflicts, has been introduced and four algorithms have been presented to generate possible solutions to a conflict. The model is illustrated by applying it to the conflict between the Obama administration and the Syrian Government in September 2013 over the destruction of Syria’s chemical weapons programme.

The author shows how different solutions, such as compromises, minimally invasive solutions or solutions compatible with certain pre-defined norms, can be generated by the model. It is shown how the model can operate in situations where the game-theoretic model fails due to a lack of information about the parties’ utility values.

The model can be used as a theoretical framework for future experimental research and/or to trace the course of particular conflict scenarios.

The model can be used as the basis for building software applications for conflict resolution practitioners, such as negotiators or mediators.

While the idea of using logic to analyse the structure of conflicts and generate possible solutions is not new to the field of conflict studies, the model presented in this paper provides a novel way of understanding conflicts for both researchers and practitioners.

The starting point of this paper is the propositional model of conflict resolution which was presented and critically discussed in Lempp (2016). Based on this model, a software implementation, called ProCON, is introduced and applied to three scenarios. The purpose of the paper is to demonstrate how ProCON can be used by negotiators and to evaluate ProCON’s practical usefulness as an automated negotiation support system.

The propositional model is implemented as a computer program. The implementation consists of an input module to enter data about a negotiation situation, an output module to generate outputs (e.g. a list of all incompatible goal pairs or a graph displaying the compatibility relations between goals) and a queries module to run queries on particular aspects of a negotiation situation.

The author demonstrates how ProCON can be used to capture a simple two-party, non-iterative prisoner’s dilemma, applies ProCON to a contract negotiation between a supplier and a purchaser of goods, and uses it to model the negotiations between the Iranian and six Western governments over Iran’s nuclear enrichment and stockpiling capacities.

A limitation of the current version of ProCON arises from the fact that the computational complexity of the underlying algorithm is EXPTIME (i.e. the computing time required to process information in ProCON grows exponentially with respect to the number of issues fed into the program). This means that computing time can be quite long for even relatively small negotiation scenarios.

The three case studies demonstrate how ProCON can provide support for negotiators in a wide range of multi-party, multi-issue negotiations. In particular, ProCON can be used to visualise the compatibility relations between parties’ goals, generate possible outcomes and solutions and evaluate solutions regarding the extent to which they satisfy the parties’ goals.

In contrast to standard game-theoretic models of negotiation, ProCON does not require users to provide data about their preferences across their goals. Consequently, it can operate in situations where no information about the parties’ goal preferences is available. Compared to game-theoretical models, ProCON represents a more general approach of looking at possible outcomes in the context of negotiations.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.