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Figure 1: FAtiMA Toolkit Components. the Slice Project. The entire toolkit is open source and is available on GitHub? and there are several resources, including Starter Kits, Demonstrations and Tutorials in FAtiMA Toolkit’s official website +

Figure 1 FAtiMA Toolkit Components. the Slice Project. The entire toolkit is open source and is available on GitHub? and there are several resources, including Starter Kits, Demonstrations and Tutorials in FAtiMA Toolkit’s official website +

Related Figures (8)

It is important to note that all “unconfirmed” Prospect-emotions can be generated even if the goal is confirmed. For example, if the agent was expecting a goal to be achieved and it fails it will generate both emotions: “Disappointment” and “Fears-Confirmed”, however, the latter will have more intensity.
It is important to note that all “unconfirmed” Prospect-emotions can be generated even if the goal is confirmed. For example, if the agent was expecting a goal to be achieved and it fails it will generate both emotions: “Disappointment” and “Fears-Confirmed”, however, the latter will have more intensity.
Figure 2: Simple dialog tree structure with each circle representing a dialogue state and eacl arrow a dialogue action.
Figure 2: Simple dialog tree structure with each circle representing a dialogue state and eacl arrow a dialogue action.
Creating this simple dialogue between a player and a character would be quite straightforward in a system that is based on dialog trees. However, if one were to use an approach based on autonomous agents then the tree itself would no longer be explicitly represented anywhere. Instead, it would have to be implicitly defined in the agents’ goals, beliefs, internal state, and actions. As such, to achieve the same effect, the author would have to configure an agent whose cognitive decisions would lead it to perform the dialogue action d3 after the player performed di and d4 after the player performed d2.
Creating this simple dialogue between a player and a character would be quite straightforward in a system that is based on dialog trees. However, if one were to use an approach based on autonomous agents then the tree itself would no longer be explicitly represented anywhere. Instead, it would have to be implicitly defined in the agents’ goals, beliefs, internal state, and actions. As such, to achieve the same effect, the author would have to configure an agent whose cognitive decisions would lead it to perform the dialogue action d3 after the player performed di and d4 after the player performed d2.
With the previous goal in mind, FAtiMA Toolkit provides an integrated authoring tool that supports the creation and configuration of scenarios by non- coders. As shown in Figure 3 this is a GUI tool with a hierarchical structure that contains several editors, a simulator and a Web API. At the top, there is a main editor where general aspects of the scenario are configured. These include the scenario’s name, a short description and a list of character profiles. On the second level of the hierarchy, there are six different editors with their own specific purpose. Figure 3: Integrated Authoring Tool - Diagram of existing components
With the previous goal in mind, FAtiMA Toolkit provides an integrated authoring tool that supports the creation and configuration of scenarios by non- coders. As shown in Figure 3 this is a GUI tool with a hierarchical structure that contains several editors, a simulator and a Web API. At the top, there is a main editor where general aspects of the scenario are configured. These include the scenario’s name, a short description and a list of character profiles. On the second level of the hierarchy, there are six different editors with their own specific purpose. Figure 3: Integrated Authoring Tool - Diagram of existing components
Figure 4: SpaceModules - Conversation screen (left); Score screen (right)
Figure 4: SpaceModules - Conversation screen (left); Score screen (right)
Figure 5: Sports Team Manager - Conversation screen
Figure 5: Sports Team Manager - Conversation screen
Figure 6: FAtiMA Virtual Reality Demo
Figure 6: FAtiMA Virtual Reality Demo
Figure 7: Mixed human-robot teams playing Sueca
Figure 7: Mixed human-robot teams playing Sueca
Related topics:
Computer ScienceHuman Computer InteractionArchitectureVirtual agent
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