Here - Agents Lab - University of Nottingham

Fig. 5. The deliberative reasoning agent in Goaland saying "Hi, Let’s take a coffee break!". In Figure 5, the action logshave been printed out to illustrate the decision making related to the task.Although this navigation task is simple, it shows that uncertain, quantitativesensory data is mapped into symbolic perceptual knowledge and allows the robotto select their actions while performing tasks in a real world environment.5 Conclusion and Future WorkThe navigation task that the robot has performed in the above section demonstratesthe feasibility of using a cognitive layer to control physical robots bymeans of agent-oriented programming. It also demonstrates that the clean separationof sub-symbolic and symbolic layers via the EIS component is feasible.Although our general architecture is similar to the layered approaches that havebeen used in many robot projects [24–27], we believe that the use of EIS providesa more principled approach to manage the interaction between sub-symbolic andsymbolic processors. Of course, it is important that the cognitive layer (agentprogram) needs adequate perceptions to make rational decisions given its specificenvironment. Our architecture provides sufficient support from various componentsdealing with Perception, Knowledge Processing, and Communication toensure this.Future work will concentrate on applying our proposed architecture for multirobotteamwork in the Block World for Teams environment [30], in which eachrobot can exchange their perceptions and share their mental states in the cognitivelayer to coordinate their actions. To this end, in the low-level layers, we willintegrate more image processing functions to endow robots with more perceptioninputs. Besides, we will also develop the adaptive ability so that robots can66