**2. System design**

For ISAC, demonstrations are segmented into behaviors in sequences. The segmented behaviors are recognized based on the pre-defined behavior categorizes. The recognized behaviors are modeled and stored in a behavior sequence. When new task constraints are given to the robot, ISAC generates same behavior sequences with new parameters on each behavior, the dynamics of which are similar to the behaviors in demonstration. These behaviors are assembled into a behavior sequence and sent to the low-level robotic control system to move the arm and control the end-effectors to complete a task.

Fig.1 is the system diagram of ISAC Cognitive Architecture, which is a multi-agents hybrid architecture. This cognitive architecture provides three control loops for cognitive control of robots: *Reactive*, *Routine* and *Deliberative.* Behaviors can be generated through this cognitive architecture. Imitation learning basically should be involved in the Deliberative control loop. Three memory components are implemented in this architecture, including: Working Memory System (WMS), Short Term Sensory Memory (STM), Long Term Memory (LTM).

Implementation of a Framework for Imitation


mathematical model.

rehearsal.

Demonstration.



Fig. 4. Control loop of the learning from demonstration.

This stage is divided into three steps: demonstration, segmentation, and recognition.

the demonstrations should be composed of the same number of behaviors.

Assumption-We assume 1) human teachers are well-trained, 2) behaviors of the same part in different demonstrations should have similar dynamics, and 3) the behavior sequences of

**2.1 Learning from demonstration** 

Demonstration

Learning on a Humanoid Robot Using a Cognitive Architecture 195

The LTM stores the memory especially the knowledge for long term use. Procedural, semantic, and episodic knowledge are stored in this component. In imitation learning, the learned skill or knowledge is stored as procedural and episodic knowledge using a

The IRS evaluates the results of the decisions made from the CEA through internal

The activity of ISAC can be divided into two stages: Learning from Demonstration, Generation by Imitating. Figure 2 displays the control loop for the first stage: Learning from

Correspondingly, the GA stores the motivations or goals of tasks in situations.

The knowledge learned from the demonstrations is stored in the Long Term Memory (LTM). When given a new task in a new situation, ISAC retrieves the knowledge from the LTM and generates a new behavior according to the sensed task information in the STM and WMS[Kawamura et al., 2008].


The PA obtains the sensory information from environment. Normally, encoders on the joints of the robot, cameras on the head of the robot, and the force feedback sensor on the wrist of the robot are implemented in this agent.

*DELIBERATION & COMMITTMENT*

Fig. 3. ISAC cognitive architecture.


The obtained information is sent to and stored in the STM. The Sensory Ego Sphere (SES) is implemented in the STM, which performs spatio-termporal coincidence detection, mediates the salience of each percept, and facilitates perceptual binding.


The WMS stores the task-related information in chunks. This component is especially important in the generation stage.


The CEA provides central processing, decision making, and control policy generating for different task goals which is stored in the Goals Agent (GA). In hierarchy architecture, this component accesses all of the sensed information and makes decision for tasks.
