To really appreciate the feedback structure of Risk the differences between the three positive feedback loops must be explored in more detail. The feedback of capturing territories to be able to build more armies is straightforward, fairly slow and involves a considerable investment of armies. Often players lose more armies in an attempt to conquer territories than they will regain with one build. This leads to the common strategy to build during multiple, consecutive turns. (In Risk players can choose to build or attack during a given turn; when they choose to build they will gain a fixed number of armies, when choosing to attack they can attack as many times as they choose during a turn. In Risk there is a rule that forces a player to attack after three consecutive turns of building.) The feedback involving the cards requires a considerably larger effort on the part of the player. Players can only gain one card during a single turn, no matter how many attacks were successful. However, depending on the cards the player draws, the return might be much higher. The feedback involving continents is very fast and with a high return. Players will receive bonus armies every turn no matter whether they choose to build or to attack. The feedback is so strong and obvious that it will typically inspire fierce counter measures from other players.
The table lists seven characteristics that, together with the determinability characteristic discussed below, form a more detailed profile of a a feedback loop. At a first glance some of these characteristics might seem overlapping, but they are not. It is easy to confuse positive feedback with constructive feedback and negative feedback with destructive feedback. However, positive destructive feedback does exist. For example, loosing pieces in a game of Chess will increase the chance of loosing more pieces and loosing the game. Likewise, the board game Power Grid employs a mechanism in which the game leaders have to invest more resources to build up and fuel their network of power plants: negative feedback on a constructive effect.
The strength of a feedback loop is an informal indication of its impact on the game. Strength cannot be attributed to a single characteristic: it is the result of several. For example, permanent feedback with a little return can have a strong effect on the game. The effects of a feedback loops on a game can drastically change with these characteristics. Feedback that is indirect, slow but with a lot of return and not durable has a strong destabilizing effect. In this way even negative feedback can be used to destabilize a system if it is applied erratically or when its effects are strong, but slow and indirect.
In many games the profile of a feedback loop is also affected by factors such as chance, player skill and social interaction. The table below lists the different types on determinability used in the Machinations framework and the icons used to denote them. These icons can be used to annotate resource connections and gates in a diagram. A single feedback loop can be affected by multiple and different types of nondeterministic resource connections or gates. For example, the feedback through cards in Risk is affected by a random gate and a random flow, increasing its unpredicatablity (see Feedback Structures in Games).
The profile of multiplayer feedback in a game that allows direct player interaction, like Risk, can change over time. As LeBlanc already pointed out, it often is negative feedback as players act stronger, or even conspire against the leader. At the same time, it can also be positive as in certain circumstances, as mentioned above, it can be beneficial to prey on the weaker player.
The skill of players in performing a particular task can also be a decisive factor in the nature of feedback, as is the case for many computer games. For example, Tetris gets more difficult as the blocks pile up, the rate at which players can get rid of the blocks is determined by their skill. Skillful players will be able to keep up with the game much longer than players with less skill. Here player skill is a factor on the operational or tactical level of the game. In games of chance, tactics, or games that involve only deterministic feedback, a whole set of strategic skills can be quite decisive for the outcome. However, that is a result of a player's understanding of the game's feedback structures as a whole, and as such it is not an element that can or needs to be modeled within the structure. This feedback loop in Tetris is also affected by randomness. The shape of the block is randomly determined by the game. Although, the skill is generally more decisive in Tetris, the player just might get lucky.
Games that feature only deterministic feedback can still show surprising unpredictable outcomes, as emergence itself can be a source of unexpected and hard to predict behavior. In fact, it is my conviction that a well-designed game is built on only a handful feedback loops and relies on chance, multiplayer dynamic, and skill only when it needs to and refrains from using randomness as an easy source of uncertainty.
A feedback loop's characteristics and determinability form the feedback's profile. While a profile like this can be very helpful in identifying the nature of feedback in a game, it does little to reveal the interaction between different feedback loops. This is where diagrams, excel. Many of the characteristics of feedback loops described above can be read from the diagrams. The effect of the feedback is directly related to the constructive or destructive nature of the feedback loop, whereas return and investment depends on the number of resources involved. A feedback loop that consists of almost only state connections and triggers, and few interactive nodes, is likely to have a high speed. Range can be read from the number of elements involved in the feedback loop, speed from the number of iterations required to activate the feedback. The return of a feedback loop must be read from the modifiers of the arrows that create the closed circuit, as some of these modifiers might be nondeterministic the return is more difficult to assess or actually becomes uncertain. The type of feedback (positive or negative) is perhaps the most difficult to read from a static representation, and requires careful inspection of the diagram, but this is possible, too. Note that the plus symbols in the diagrams do not indicate positive feedback, only that there is positive correlation between the number of resources in the pool and the label it is affecting. A positive correlation can induce negative or positive feedback.