Animated agent technology has been rapidly developed to provide ubiquitously psychological and functional benefits for fulfilling communicative goals. However, the character motions of most character-centered models based on pre-stored movement, finite state machine and scripted conditional logic are generally restrictive. The major drawback lies in the lack of maturity of integrating the elements between personality, emotion and behaviour. To bridge the gap between cognitive and behavioural elements, we examine the connections between human personality, emotion, movement and cartoon modeling for the agent design. Human personality and emotional behaviour are the essences in the recognition of a believable synthetic character. Personality and emotion come from the storylines and result in characters’ motions. Cartoon animations successfully engage the audience and create emotional connections with the spectators. However, even a sophisticated animator often faces some difficulties while performing a very laborious task to simulate an emotion- and personality-rich character. This thesis focuses on exploring effective techniques to extract personality and emotion features for a high-level control of character movements. A hierarchical fuzzy rule-based system was constructed, in which personality and emotion were mapped into the body’s movement zones of a character. This facilitates agent designers to control the personality and emotion of a dynamic synthetic character. The system was then applied to a Narrative Intelligent system and extended to an Ambient Intelligent environment. An innovative storyboard-structured storytelling method was devised by using story scripts and action descriptions in a form similar to the content description of storyboards to predict specific personality and emotion. As software or device agents evolve into the Ambient Intelligence, new concepts for effective agent presentations and delegating control are necessary to minimise the human’s tasks and interventions in the complex and dynamic environment. A novel customizable personalised agent framework was developed by utilising the spirit of cartoon animation to match each user’s profile in the form of a cartoon reciprocal agent. As a result, users could explicitly modify personality and emotion values to change the psychology traits of the agent, which would affect their appearance and behaviour through body posture expression. An evaluation of the system was conducted to verify the effectiveness and the applicability in both Narrative and Ambient intelligent agent frameworks. The significance of this research is that applying higher cognitive factors to animated characters can lead to a better animation design tool and reduce strenuous animation production efforts in agent designs. It will also enable animated characters to embody more adaptive, flexible and stylised performance.