By Koen V. Hindriks, Birna van Riemsdijk, Tristan Behrens, Rien Korstanje (auth.), Frank Dignum (eds.)
While latest online game engines and multi-agent systems cross-fertilize one another to a point, the applied sciences utilized in those parts will not be without difficulty suitable because of a few modifications of their basic issues. the place video game engines prioritize potency and primary keep an eye on, multi-agent systems concentrate on agent autonomy and complicated communique functions. This quantity provides an outline of the present state-of-the-art for individuals wishing to mix agent expertise with (serious) video games.
This state of the art survey features a choice of papers provided at AGS 2010; the second one overseas Workshop on brokers for video games and Simulations, hung on may possibly 10, 2010, in Toronto, in addition to prolonged models of papers from different workshops and from the AAMAS convention. The 14 papers are geared up in 3 topical sections concentrating on architectures combining brokers and online game engines, at the education elements of the video games, on social and organizational points of video games and brokers, respectively.
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Additional info for Agents for Games and Simulations II: Trends in Techniques, Concepts and Design
The proposed architecture is shown in Figure 2. It is composed of two layers: the cognitive layer of the IVA, realized in the multi-agent system, and the physical layer, realized in the game engine. Fig. 2. IVA Architecture In the cognitive layer the full behavior of an agent comprises two modules also known as capabilities: an agent-generic capability and an agent-speciﬁc capability. The agent-generic capability is shared by all agents and consists of basic humanoid behaviors required in the simulated domain like agent communication or object interactions like knowing how to use a phone.
In the rest of this section, Pogamut’s generic agent architecture implementing the ideas from Sec. 3 and 4 will be introduced and exemplified on an implemented AgentSpeak(L)–based agent , called here AS agent, demonstrating Pogamut’s technical flexibility. 1 Architecture of Pogamut Agent The generic architecture of Pogamut 3 agent is depicted on Figure 3. The architecture introduces a set of layers that shields an agent DMS from the low-level communication with a GE, taking care of the load, update, requested and requests arrows from Figure 2.
Similarly, a ray cast request will finish well before the A* algorithm finds out that a requested path does not exist. Two major issues linked to the requests are to be handled by an agent DMS. Firstly, the DMS should be able to handle the lag between a computation request and its returned result. Especially the path requests should be made in advance. Secondly, GEs may not report success or failure of an action. ). If a deviation from an expected result is detected, actions to compensate should take place.