In this chapter we present an Ontology Design Pattern for the definition of situation-driven behaviour selection and arbitration models for cognitive agents. The proposed pattern relies on the descriptions and situations ontology pattern, combined with a frame-based representation scheme. Inspired by the affordance theory and behaviour-based robotics principles, our reference model enables the definition of weighted relationships, or affordances, between situations (representing agent's perception of the environmental and social context) and agent's functional and behavioral abilities. These weighted links serve as a basis for supporting runtime task selection and arbitration policies, to dynamically and contextually select agent's behaviour. The pattern is at the heart of the behaviour-based cognitive approach adopted in the EU H2020 MARIO project for the design of an autonomous service robot (i.e., the cognitive agent) to support elderly people with cognitive impairments.