Contributed by: Giovanni Pezzulo, ISTC-CNR, Rome, Italy

Introduction
The affordance concept, from its beginnings, has been a misty one. Despite the existence of a large body of literature on the concept, upon reviewing the literature, one encounters different façades of this term, sometimes contradictory, rather like the description of an elephant by the six blind men in the famous Indian tale. In this briefing we review this inspiring notion from its conception by J.J. Gibson to its uses in different fields.

The Notion of Affordances
In his early studies on visual perception, J.J. Gibson tried to understand how the “meanings” of the environment were specified in perception for certain behaviors. To this end, he identified optical variables in the perceptual data that are meaningful. Based on the studies of meaningful optical variables and the Gestaltist conception of the immediate perception of meanings of the things, J.J. Gibson built his own theory of perception and coined the term affordance to refer to the action possibilities that objects offer to an organism in an environment. Although one may be inclined to talk about affordances as if they were simply properties of the environment, they are not. J.J. Gibson believed that affordances are directly perceivable (a.k.a. direct perception) by the organism, thus the meaning of the objects in the environment are directly apparent to the agent acting in it. This was different from the contemporary view of the time that the meaning of objects were created internally with further “mental calculation” of the otherwise meaningless perceptual data.

To date, there has been much confusion regarding the concept of affordances. We believe that there are a number of reasons for this confusion:

1. J.J. Gibson’s own understanding of affordances evolved over time.
2. J.J. Gibson’s own ideas on the concept were not finalized during his lifetime, as Jones concludes in [Jones, 2003].
3. J.J. Gibson’s idea of affordance can be fully understood only in contrast to the background of contemporary ideas on perception, rather than in isolation.
4. J.J. Gibson defined affordances as a concept that relates the perception of an organism to its action, whereas his main research interest laid in the perception aspect.
5. J.J. Gibson’s own discussions on affordances were often blended with his work on visual perception

Quotations from J.J. Gibson
“The affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill. The verb to afford is found in the dictionary, but the noun affordance is not. I have made it up. I mean by it something that refers to both the environment and the animal in a way that no existing term does. It implies the complementarity of the animal and the environment.”

“... an affordance is neither an objective property nor a subjective property; or both if you like. An affordance cuts across the dichotomy of subjective-objective and helps us to understand its inadequacy. It is equally a fact of the environment and a fact of behavior. It is both physical and psychical, yet neither. An affordance points bothways, to the environment and to the observer.”

“The perceiving of an affordance is not a process of perceiving a value-free physical object to which meaning is somehow added in a way that no one has been able to agree upon; it is a process of perceiving a value-rich ecological object.”

“The theory of affordances rescues us from the philosophical muddle of assumingfixed classes of objects, each defined by its common features and then given a name...You do not have to classify and label things in order to perceive what they afford.”

(J.J. Gibson, 1979/1986)

Affordance-Related Research in Ecological Psychology
Following the formulation of the theory of affordances, the Ecological Psychology community started to conduct experiments in order to verify that, people are able to perceive the affordances of the environment, and to understand the mechanisms underlying this perception. These experiments [Warren, 1984, Warren and Whang, 1987,Mark, 1987, Gibson et al., 1987, Kinsella-Shaw et al., 1992, Chemero, 2000] aimed to show that organisms (mostly human) can perceive whether a specific action is do-able or not-do-able in an environment. This implies that, what we perceive is not necessarily objects (e.g. stairs, doors, chairs), but the action possibilities (e.g. climbable, passable, sitable) offered by the environment. Although the number of these experiments is quite high, their diversity is rather narrow. They constitute a class of experiments characterized by two main points: taking the ratio of an environmental measure and a bodily measure of the human subject; and, based on the value of this ratio, making a binary judgment about whether a specific action is do-able or not.

All these experiments were performed in a one shot manner, and the subject is either stationary or moving [Warren and Whang, 1987], either monocular or binocular vision [Cornus et al., 1999] is employed, either haptic or visual information [Gibson et al., 1987] is used, either the critical or optimal points [Warren, 1984] are determined, and either searching for affordance or change in the layout of an affordance [Chemero et al., 2003] is examined. An overview of the experiments shows that they are mostly focused on the perception aspect of affordances. Other cognitive processes such as learning, high level reasoning and inference mechanisms are not the subjects of these experiments, and the link between affordances and these higher level processes is not discussed.

Affordance-Related Research in Cognitive Science
E.J. Gibson defined learning as a perceptual process and named her theory of learning “perceptual learning”. She argued that learning is neither the construction of representations from smaller pieces, nor the association of a response to a stimulus. Instead, she claimed, learning is “discovering distinctive features and invariant properties of things and events” [Gibson, 2000] or “discovering the information that specifies an affordance” [Gibson, 2003].

Studies on affordance, reviewed so far, have not provided any ideas regarding its relation to other higher-level cognitive processes. Neisser, in his “Cognition and Reality” book [Neisser, 1976], tried to place affordances and direct perception into a complete cognitive system model and tried to link them with other cognitive processes such as recognition. According to him, J.J. Gibson was right in stating that the meanings of the environment are directly available, and “information is not processed, but it is directly picked up since it is already there (in the light)”. Invariance attuned detectors are used for this purpose. However, he claimed, the Gibsonian view of affordances of perception is inadequate, since “it says so little about perceiver’s contribution to the perception act”. Instead, he suggests a perceptual system where a cycling activity continuous over time and space occurs. Neisser also tried to integrate both constructive and direct theories of perception. As a result, in [Neisser, 1994], he constructed a three-layered perceptual system, whose first and third layers correspond to direct perception and recognition, respectively.

Affordance-Related Research in Neurophysiology and Neuropsychology
In [Norman, 2002], J. Norman, in a similar vein to Neisser, “attempted to reconcile the constructivist and ecological approaches” in one bigger system, using studies from neurophysiological and neuropsychological studies. Based on evidence from human dorsal and ventral systems, he suggested a perceptual system where two different and interacting visual systems work. According to J. Norman, it is straightforward to conclude that “the pickup of affordances can be seen as the prime activity of the dorsal system”.

Another set of findings of neurophysiological and neuropsychological research that is also associated with the idea of affordances came from studies on mirror and canonical neurons which were discovered in the pre-motor cortex of the monkey brain. During experiments with monkeys [Rizzolatti et al., 1996] (later similar findings were also found for human subjects [Fadiga et al., 1995]), mirror neurons fired both when the monkey was grasping an object, and when the monkey was watching somebody else do the grasping. Rizzolatti and Gentilucci [Rizzolatti and Gentilucci, 1988] discovered that canonical neurons, normally considered to be motor neurons for grasping actions, would fire when the subject does not execute a grasping action, but only sees a graspable object. Their discovery supports the view that says action and perception are closely related. In [Humphreys, 2001], Humphreys showed that, when presented with a tool, some patients, who lacked the ability to name the tool, had no problem in gesturing the appropriate movement for using it. According to Humphreys, this suggested a direct link from the visual input to the motor actions that is independent from more abstract representations of the object, e.g. its name.

Affordance-Related Research in Autonomous Robotics
The concept of affordances is highly related to autonomous robot control and it has influenced studies in this field. We believe that, for a proper discussion of the relationship of the affordance concept to robot control, the similarity of the arguments of J.J. Gibson’s theory and reactive/behavior-based robotics should first be noted. The concept of affordances and behavior-based robotics emerged in very similar ways as opposing suggestions to the then dominant paradigms in their fields. They are both constructed based on the critisism of the dominant models and methods which favored modeling and inference. They both defend a direct relationship between agent and its environment, and tight coupling between perception and action. They are both on the side of “picking up only relevant information from the environment”, and perceiving the environment economically.

Some roboticists have already been explicitly using ideas on affordances in designing behavior-based robots. For example, Murphy [Murphy, 1999] suggested that robotic design can benefit from ideas in the theory of affordances such that complex perceptual modeling can be eliminated without loss in capabilities. She studied three case studies and drew attention to the importance of the ecological niche in the design of behaviors. Likewise, Duchon et al. [Duchon et al., 1998] benefited from J.J. Gibson’s ideas on direct perception and optic flow in the design of behaviors and coined the term Ecological Robotics for the practice of applying ecological principles to the design of mobile robots.

The use of affordances within Autonomous Robotics is mostly confined to behavior-based control of the robots, and its use in deliberation remains a rather unexplored area. In Cognitive Science, some cognitive models related affordances only with low-level processes [Norman, 2002], others viewed affordances as a part of a complete cognitive model [Gibson, 2000, Neisser, 1994, MacDorman, 2000]. Similarly, in robotics, some hybrid architectures inherit properties related to affordances only at their reactive layer [Arkin and Balch, 1997, Connell, 1992]. Recently a number of robotic studies focused on the learning of affordances in robots. These studies mainly tackled two major aspects. In one aspect, affordance learning is referred to as the learning of the consequences of a certain action in a given situation [Fitzpatrick et al., 2003, Stoytchev, 2005b, Stoytchev, 2005a]. In the other, studies focus on the learning of the invariant properties of environments that afford a certain behavior [MacDorman, 2000, Cos-Aguilera et al., 2003, Cos-Aguilera et al., 2004]. Studies in this latter group also relate these properties to the consequences of applying a behavior, but these consequences are in terms of the internal values of the agent, rather than changes in the physical environment.

Affordances in Computer Games and Virtual Reality Applications
In computer games and virtual reality applications in general, the concept of affordances is used in two ways; as a technical construct and from the design point of view. Technically, the notion of affordances inspires the method of construction of representations of possible actions a virtual character can execute in a particular virtual environment. The tenet of this thread of thinking can be best illustrated on so called ''smart objects'' [Kallmann and Thalmann, 1998]. A smart object is an entity with the ability to describe in detail its functionality, its possible interactions as well as behaviour of an interacting virtual character. We can say, that the purpose of a smart object is "engraved" in it directly. Using smart objects, the virtual world can be described in the terms of a purpose-oriented language, and since virtual humans can directly perceive this purpose, they do not need to infer it neither from a symbolical representation nor low-level sensory data. It follows that a (smart) object can be loaded into the virtual world as a plug-in and a virtual character can interact with it automatically.

The limitation of classical smart objects is that they encapsulate only low-level “graphical” information such as a v-human’s position during execution of an action, or a desired hand-shape. Ciger [2005] extended smart objects so that they can pass on planning operators to a virtual character, a method allowing for using of a planning algorithm. Another limitation of smart objects is that they can not describe interaction among more objects (hammering using a hammer and a nail). This issue was addressed by Brom et al. [2006], who introduced the concept of ''smart actions'' [see also Brom, 2007]. In many computer games, high-level semantic terrain representations are used, sometimes called semantic marks. The most classical semantic marks are way-points and navigation meshes used for the purposes of path-planning. However, more complicated information can be coded, e.g. "from this place you can jump" or "shoot" [Isla, 2005].

Note that smart objects, smart actions and semantic marks are typically specified in advance by a designer, that is, they are really a technique for representation, not a desired outcome of a learning process (compare e.g. with affordances used in robotics).

In the domain of entertainment and educational applications, affordances have been also conceived more theoretically as a construct for mediating author’s intentions and users’ experiences (through virtual reality). Roughly, the idea is that a device – a computer plus an authoring tool – affords to the author a process of construction of a virtual reality application through which the author can mediate to the user its intentions. That is, the virtual reality affords to the user by means of some specific clues to experience situations intended by the author. See e.g. [Mateas, 2002] for more on this concept.

Prior Formalizations of Affordances
One of the earliest attempts to formalize affordances came from Turvey [Turvey, 1992]. In his formalism, Turvey defined an affordance as a disposition. Here, a disposition is a property of a thing that is a potential, a possibility. These potentials become actualized if they combine with their complements. In this formalism, although the actualization of affordances requires an interaction of an agent on the environment to produce a new dynamics, Turvey explicitly attached affordances to the environment that the organism is acting in. A criticism of Turvey’s formalism came from Stoffregen [Stoffregen, 2003]. His view places affordances in the organism-environment system as a whole instead of defining it as a property of the environment: “Affordances are properties of the animal-environment system, that is, that they are emergent properties that do not inhere in either the environment or the animal.” Chemero [Chemero, 2003] also criticized Turvey’s view which placed affordances in the environment regarding them as environmental properties. Partially in agreement with Stoffregen’s proposal, Chemero suggested that: “Affordances are relations between the abilities of organisms and features of the environment.” One of the main differences between the two similar formalisms of Stoffregen and Chemero, which both define affordances at the organism-environment scale, is that while Stoffregen’s definition of affordance does not include the behavior exploiting the affordance, Chemero’s definition does include it.

Steedman’s formalization [Steedman, 2002a; Steedman 2002b] skips the perceptual aspect of affordances (e.g. the invariants of the environment that help the agent perceive the affordances, and the nature of these invariants and the relation of them to the bodily properties of the agent etc.), but instead it focuses on developing a representation where object schemas are defined in relation to the events and actions that they are involved in. For instance, Steedman suggests that a door is linked with the actions of ‘pushing’ and ‘going-through’, and the pre-conditions and consequences of applying these actions to the door. The different actions that are associated with a particular kind of object constitute the Affordance-set of that object schema, and this set can be populated via learning. This makes the formalization also suitable for planning, for which Steedman argues that reactive/forward-chaining planning is the best candidate. Steedman’s formalization resembles formalizations developed recently for the purposes of virtual reality applications [Ciger et al., 2005; Brom, 2007]. These formalizations are, as far as we know, the first attempts to develop a formalization of affordances allowing for logical/computational manipulation and planning. The approach of Brom allows also for developing a robust [[Level of Detail AI for Computer Games|level-of-detail mechanism for action selection]] of virtual characters.

To summarize, it can be said that Stoffregen’s and Chemero’s formalizations, by defining affordances as a relation on the scale of organism-environment system, differ from Turvey’s formalization which defines affordances as environmental properties. But there are also differences between Chemero’s and Stoffregen’s definitions, one of them being the inclusion of behaviors in the definition of affordances in Chemero’s formalization. Steedman’s formalization differs from the other three formalizations by providing an explicit link to action possibilities offered by the environment, and by proposing the use of the concept in planning.

Conclusion
We would like to note that affordance theory has mostly been used as a source of inspiration in robotics. Most of the studies reviewed above preferred to refer to J.J. Gibson’s original ideas as formulated in his books, ignoring modern discussions on the concept. As a result, only certain aspects of the theory have been used, and no attempts to consider the implications of the whole theory towards autonomous robot control have been made. In [Sahin et al.], the notion of affordances is formalized to provide a base over which it can be used in different aspects of autonomous robot control.

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Acknowledgement
This work was partly funded by the European Commission's 6th Framework Programme IST Project: euCognition Network Action NA_119-2 -- ABiALS 2008: the fourth workshop on Anticipatory Behavior in Adaptive Learning Systems